An assessment of self-reported physical activity instruments in young people for population surveillance: Project ALPHA

<p>Abstract</p> <p>Background</p> <p>The assessment of physical activity is an essential part of understanding patterns and influences of behaviour, designing interventions, and undertaking population surveillance and monitoring, but it is particularly problematic when using self-report instruments with young people. This study reviewed available self-report physical activity instruments developed for use with children and adolescents to assess their suitability and feasibility for use in population surveillance systems, particularly in Europe.</p> <p>Methods</p> <p>Systematic searches and review, supplemented by expert panel assessment.</p> <p>Results</p> <p>Papers (n = 437) were assessed as potentially relevant; 89 physical activity measures were identified with 20 activity-based measures receiving detailed assessment. Three received support from the majority of the expert group: Physical Activity Questionnaire for Children/Adolescents (PAQ-C/PAQ-A), Youth Risk Behaviour Surveillance Survey (YRBS), and the Teen Health Survey.</p> <p>Conclusions</p> <p>Population surveillance of youth physical activity is strongly recommended and those involved in developing and undertaking this task should consider the three identified shortlisted instruments and evaluate their appropriateness for application within their national context. Further development and testing of measures suitable for population surveillance with young people is required.</p

Family influences on children's physical activity and fruit and vegetable consumption

Background : There is evidence of a clustering of healthy dietary patterns and physical activity among young people and also of unhealthy behaviours. The identification of influences on children\u27s health behaviors, particularly clustered health behaviors, at the time at which they develop is imperative for the design of interventions. This study examines associations between parental modelling and support and children\u27s physical activity (PA) and consumption of fruit and vegetables (FV), and combinations of these behaviours.Methods : In 2002/3 parents of 775 Australian children aged 10&ndash;12 years reported how frequently their child ate a variety of fruits and vegetables in the last week. Children wore accelerometers for eight days during waking hours. Parental modelling and parental support (financial and transport) were self-reported. Binary logistic and multinomial logistic regression analyses examined the likelihood of achieving &ge; 2 hours of PA per day (high PA) and of consuming &ge; 5 portions of FV per day (high FV) and combinations of these behaviors (e.g. high PA/low FV), according to parental modelling and support.Results : Items of parental modelling and support were differentially associated with child behaviours. For example, girls whose parents reported high PA modelling had higher odds of consuming &ge; 5 portions of FV/day (OR = 1.95, 95% CI = 1.32&ndash;2.87, p &lt; 0.001). Boys whose parents reported high financial support for snacks/fast foods had higher odds of having \u27high PA/low FV\u27 (OR = 2.0, 95% CI = 1.1&ndash;3.7).Conclusion : Parental modelling of and support for physical activity and fruit and vegetable consumption were differentially associated with these behaviours in children across behavioural domains and with combinations of these behaviours. Promoting parents\u27 own healthy eating and physical activity behaviours as well encouraging parental modelling and support of these behaviours in their children may be important strategies to test in future research.<br /

Family circumstance, sedentary behaviour and physical activity in adolescents living in England: Project STIL

<p>Abstract</p> <p>Background</p> <p>Identification of non-modifiable correlates of physical activity and sedentary behaviour in youth contributes to the development of effective targeted intervention strategies. The purpose of this research was to examine the relationships between family circumstances (e.g. socio-economic status, single vs. dual parent household, presence/absence of siblings) and leisure-time physical activity and sedentary behaviours in adolescents.</p> <p>Methods</p> <p>A total of 1171 adolescents (40% male; mean age 14.8 years) completed ecological momentary assessment diaries every 15 minutes for 3 weekdays outside of school hours and 1 weekend day. Analysed behaviours were sports/exercise, active travel, TV viewing, computer use, sedentary socialising (hanging-out, using the telephone, sitting and talking) and total sedentary behaviour. Linear regression was employed to estimate levels of association between individual family circumstance variables and each behaviour.</p> <p>Results</p> <p>Compared to girls from higher socioeconomic status (SES) groups, girls from low SES groups reported higher weekend TV viewing and higher weekday total sedentary behaviour. For boys, single parent status was associated with greater total sedentary behaviour compared to those from dual parent households. Boys and girls from low socio-economic neighbourhoods reported lower participation in sports/exercise compared to those living in higher socio-economic neighbourhoods.</p> <p>Conclusion</p> <p>Associations were not consistent across behaviours or between genders. Overall, findings indicate that boys from single parent households and girls from low socio-economic families may be at increased risk of high sedentary behaviour. Those living in low socioeconomic neighbourhoods may be at increased risk of reduced participation in sports and exercise.</p

Patterns of adolescent physical activity and dietary behaviours

<p>Abstract</p> <p>Background</p> <p>The potential synergistic effects of multiple dietary and physical activity behaviours on the risk of chronic conditions and health outcomes is a key issue for public health. This study examined the prevalence and clustering patterns of multiple health behaviours among a sample of adolescents in the UK.</p> <p>Methods</p> <p>Cross-sectional survey of 176 adolescents aged 12–16 years (49% boys). Adolescents wore accelerometers for seven days and completed a questionnaire assessing fruit, vegetable, and breakfast consumption. The prevalence of adolescents meeting the physical activity (≥ 60 minutes moderate-to-vigorous physical activity/day), fruit and vegetable (≥ 5 portions of FV per day) and breakfast recommendations (eating breakfast on ≥ 5 days per week), and clustering patterns of these health behaviours are described.</p> <p>Results</p> <p>Boys were more active than girls (p < 0.001) and younger adolescents were more active than older adolescents (p < 0.01). Boys ate breakfast on more days per week than girls (p < 0.01) and older adolescents ate more fruit and vegetables than younger adolescents (p < 0.01). Almost 54% of adolescents had multiple risk behaviours and only 6% achieved all three of the recommendations. Girls had significantly more risk factors than boys (p < 0.01). For adolescents with two risk behaviours, the most prevalent cluster was formed by not meeting the physical activity and fruit and vegetable recommendations.</p> <p>Conclusion</p> <p>Many adolescents fail to meet multiple diet and physical activity recommendations, highlighting that physical activity and dietary behaviours do not occur in isolation. Future research should investigate how best to achieve multiple health behaviour change in adolescent boys and girls.</p

Modelling the Reallocation of Time Spent Sitting into Physical Activity: Isotemporal Substitution vs. Compositional Isotemporal Substitution.

Isotemporal substitution modelling (ISM) and compositional isotemporal modelling (CISM) are statistical approaches used in epidemiology to model the associations of replacing time in one physical behaviour with time in another. This study's aim was to use both ISM and CISM to examine and compare associations of reallocating 60 min of sitting into standing or stepping with markers of cardiometabolic health. Cross-sectional data collected during three randomised control trials (RCTs) were utilised. All participants (n = 1554) were identified as being at high risk of developing type 2 diabetes. Reallocating 60 min from sitting to standing and to stepping was associated with a lower BMI, waist circumference, and triglycerides and higher high-density lipoprotein cholesterol using both ISM and CISM (p < 0.05). The direction and magnitude of significant associations were consistent across methods. No associations were observed for hemoglobin A1c, total cholesterol, or low-density lipoprotein cholesterol for either method. Results of both ISM and CISM were broadly similar, allowing for the interpretation of previous research, and should enable future research in order to make informed methodological, data-driven decisions

"I'm on it 24/7 at the moment": A qualitative examination of multi-screen viewing behaviours among UK 10-11 year olds

Background: Screen-viewing has been associated with increased body mass, increased risk of metabolic syndrome and lower psychological well-being among children and adolescents. There is a shortage of information about the nature of contemporary screen-viewing amongst children especially given the rapid advances in screen-viewing equipment technology and their widespread availability. Anecdotal evidence suggests that large numbers of children embrace the multi-functionality of current devices to engage in multiple forms of screen-viewing at the same time. In this paper we used qualitative methods to assess the nature and extent of multiple forms of screen-viewing in UK children. Methods: Focus groups were conducted with 10-11 year old children (n = 63) who were recruited from five primary schools in Bristol, UK. Topics included the types of screen-viewing in which the participants engaged; whether the participants ever engaged in more than one form of screen-viewing at any time and if so the nature of this multiple viewing; reasons for engaging in multi-screen-viewing; the room within the house where multi-screen-viewing took place and the reasons for selecting that room. All focus groups were transcribed verbatim, anonymised and thematically analysed. Results: Multi-screen viewing was a common behaviour. Although multi-screen viewing often involved watching TV, TV viewing was often the background behaviour with attention focussed towards a laptop, handheld device or smart-phone. There were three main reasons for engaging in multi-screen viewing: 1) tempering impatience that was associated with a programme loading; 2) multi-screen facilitated filtering out unwanted content such as advertisements; and 3) multi-screen viewing was perceived to be enjoyable. Multi-screen viewing occurred either in the child's bedroom or in the main living area of the home. There was considerable variability in the level and timing of viewing and this appeared to be a function of whether the participants attended after-school clubs. Conclusions: UK children regularly engage in two or more forms of screen-viewing at the same time. There are currently no means of assessing multi-screen viewing nor any interventions that specifically focus on reducing multi-screen viewing. To reduce children's overall screen-viewing we need to understand and then develop approaches to reduce multi-screen viewing among children.This project was funded by a small research grant from the Faculty of Social Sciences of Law at the University of Bristol. This report is also research arising from a Career Development Fellowship (to Dr Jago) supported by the National Institute for Health Research. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health

Age-related change in sedentary behavior during childhood and adolescence: A systematic review and meta-analysis.

Funder: University of East Anglia, Faculty of Medicine and Health SciencesSedentary behaviors are highly prevalent in youth and may be associated with markers of physical and mental health. This systematic review and meta-analysis aimed to quantify the age-related change in sedentary behavior during childhood and adolescence. Ten electronic databases were searched. Inclusion criteria specified longitudinal observational studies or control group from an intervention; participants aged ≥5 and ≤18 years; a quantitative estimate of the duration of SB; and English language, peer-reviewed publication. Meta-analyses summarized weighted mean differences (WMD) in device-assessed sedentary time and questionnaire-assessed screen-behaviors over 1-, 2-, 3-, or more than 4-year follow-up. Effect modification was explored using meta-regression. Eighty-five studies met inclusion criteria. Device-assessed sedentary time increased by (WMD 95% confidence interval [CI]) 27.9 (23.2, 32.7), 61.0 (50.7, 71.4), 63.7 (53.3, 74.0), and 140.7 (105.1, 176.4) min/day over 1-, 2-, 3-, and more than 4-year follow-up. We observed no effect modification by gender, baseline age, study location, attrition, or quality. Questionnaire-assessed time spent playing video games, computer use, and a composite measure of sedentary behavior increased over follow-up duration. Evidence is consistent in showing an age-related increase in various forms of sedentary behavior; evidence pertaining to variability across socio-demographic subgroups and contemporary sedentary behaviors are avenues for future research

Age-related change in sedentary behavior during childhood and adolescence: A systematic review and meta-analysis.

Funder: University of East Anglia, Faculty of Medicine and Health SciencesSedentary behaviors are highly prevalent in youth and may be associated with markers of physical and mental health. This systematic review and meta-analysis aimed to quantify the age-related change in sedentary behavior during childhood and adolescence. Ten electronic databases were searched. Inclusion criteria specified longitudinal observational studies or control group from an intervention; participants aged ≥5 and ≤18 years; a quantitative estimate of the duration of SB; and English language, peer-reviewed publication. Meta-analyses summarized weighted mean differences (WMD) in device-assessed sedentary time and questionnaire-assessed screen-behaviors over 1-, 2-, 3-, or more than 4-year follow-up. Effect modification was explored using meta-regression. Eighty-five studies met inclusion criteria. Device-assessed sedentary time increased by (WMD 95% confidence interval [CI]) 27.9 (23.2, 32.7), 61.0 (50.7, 71.4), 63.7 (53.3, 74.0), and 140.7 (105.1, 176.4) min/day over 1-, 2-, 3-, and more than 4-year follow-up. We observed no effect modification by gender, baseline age, study location, attrition, or quality. Questionnaire-assessed time spent playing video games, computer use, and a composite measure of sedentary behavior increased over follow-up duration. Evidence is consistent in showing an age-related increase in various forms of sedentary behavior; evidence pertaining to variability across socio-demographic subgroups and contemporary sedentary behaviors are avenues for future research

Associations of parental physical activity trajectories with offspring's physical activity patterns from childhood to middle adulthood: The Young Finns Study

We investigated the association of parental physical activity (PA) trajectories with offspring's youth and adult PA. Self-reported PA data were extracted from the Young Finns Study with three follow-ups for parents between 1980 and 1986 and nine follow-ups for their offspring in youth between 1980 and 2011 (aged 9-39 years, n = 2402) and in adulthood in 2018. Accelerometer-derived PA was quantified in 2018-2020 (aged 43-58 years, n = 1134). Data were analyzed using mixture models and conducted in 2022. We identified three trajectories for fathers and mothers (high-stable activity, 20.2%/16.6%; moderate-stable activity, 50.5%/49.6%; and low-stable activity, 29.4%/33.7%) and four for youth male and female offspring (persistently active, 13.4%/5.1%; increasingly active, 32.1%/43.1%; decreasingly active, 14.4%/12.6%; and persistently low-active, 40.1%/39.1%). Compared to low-stable active parents, high-stable active fathers had a higher probability of having their sons and daughters classified as persistently active, increasingly active, and decreasingly active in youth (Brange = 0.50-1.79, all p range = 0.63-1.16, all p < 0.009). Fathers' and mothers' high-stable activity was associated with higher self-reported PA of adult offspring than parental low-stable activity. Persistently active and increasingly active offspring in youth accumulated more adult total PA, moderate-to-vigorous PA, step counts, and self-reported PA than persistently low-active ones (all p < 0.036). Parental persistent PA, particularly paternal persistent PA, predicts offspring's PA concurrently and prospectively. Increasing and maintaining PA in youth predicts higher PA levels in midlife

Implementation and engagement of the SMART Work & Life sitting reduction intervention: an exploratory analysis on intervention effectiveness

Background: To enhance the impact of interventions, it is important to understand how intervention engagement relates to study outcomes. We report on the level of implementation and engagement with the SMART Work & Life (SWAL) programme (delivered with (SWAL plus desk) and without a height-adjustable desk (SWAL)) and explore the effects of different levels of this on change in daily sitting time in comparison to the control group. Methods: The extent of intervention delivery by workplace champions and the extent of engagement by champions and participants (staff) with each intervention activity was assessed by training attendance logs, workplace champion withdrawal dates, intervention activities logs and questionnaires. These data were used to assess whether a cluster met defined criteria for low, medium, or high implementation and engagement or none of these. Mixed effects linear regression analyses tested whether change in sitting time varied by: (i) the number of intervention activities implemented and engaged with, and (ii) the percentage of implementation and engagement with all intervention strategies. Results: Workplace champions were recruited for all clusters, with 51/52 (98%) attending training. Overall, 12/27 (44.4%) SWAL and 9/25 (36.0%) SWAL plus desk clusters implemented all main intervention strategies. Across remaining clusters, the level of intervention implementation varied. Those in the SWAL (n = 8 (29.6%) clusters, 80 (32.1%) participants) and SWAL plus desk (n = 5 (20.0%) clusters, 41 (17.1%) participants) intervention groups who implemented and engaged with the most intervention strategies and had the highest percentage of cluster implementation and engagement with all intervention strategies sat for 30.9 (95% CI -53.9 to -7.9, p = 0.01) and 75.6 (95% CI -103.6 to -47.7, p < 0.001) fewer minutes/day respectively compared to the control group at 12 month follow up. These differences were larger than the complete case analysis. The differences in sitting time observed for the medium and low levels were similar to the complete case analysis. Conclusions: Most intervention strategies were delivered to some extent across the clusters although there was large variation. Superior effects for sitting reduction were seen for those intervention groups who implemented and engaged with the most intervention components and had the highest level of cluster implementation and engagement. Trial Registration: ISRCTN11618007. Registered on 24 January 2018. https://www.isrctn.com/ISRCTNISRCTN11618007