22 research outputs found

    Socioeconomic position and childhood sedentary time: evidence from the PEACH project

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    BACKGROUND: Associations between socioeconomic position (SEP) and sedentary behaviour in children are unclear. Existing studies have used aggregate measures of weekly sedentary time that could mask important differences in the relationship between SEP and sedentary time at different times of the day or between weekdays and weekend days. These studies have also employed a variety of measures of SEP which may be differentially associated with sedentary time. This paper examines associations of multiple indicators of SEP and accelerometer-measured, temporally specific, sedentary time in school children. METHODS: Between 2006 and 2007 sedentary time data (minutes spent below 100 accelerometer counts per minute) for weekdays before-school (7.00-8.59AM), during school-time (9.00AM-2.59PM) and after-school (3.00PM-11.00PM), and weekend days were recorded for 629 10–11 year old children using accelerometers. Ordinary least squares regression was used to examine associations with 5 indicators of SEP (area deprivation, annual household income, car ownership, parental education and access to a private garden). Covariates were; gender, BMI, minutes of daylight, accelerometer wear time and school travel method. Analyses were conducted in 2012. RESULTS: Following adjustments for covariates, having a parent educated to university degree level was associated with more minutes of school (5.87 [95% CI 1.72, 10.04]) and after-school (6.04 [95% CI 0.08, 12.16]) sedentary time. Quartiles of area deprivation (most to least deprived) were positively associated with after-school (Q2: 4.30 [95% CI −6.09, 14.70]; Q3: 10.77 [95% CI 0.47, 21.06]; Q4: 12.74 [95% CI 2.65, 22.84]; P(trend) = 0.04) and weekend (Q2: 26.34 [95% CI 10.16, 42.53]; Q3: 33.28 [95% CI 16.92, 49.65]; Q4: 29.90 [95% CI 14.20, 45.60]; P(trend) = 0.002) sedentary time. Having a garden was associated with less sedentary time after-school (−14.39 [95% CI −25.14, -3.64]) and at weekends (−27.44 [95% CI −43.11, -11.78]). CONCLUSIONS: Associations between SEP and children’s sedentary-time varied by SEP indicator and time of day. This highlights the importance of measuring multiple indicators of SEP and examining context specific sedentary time in children in order to fully understand how SEP influences this behaviour. Further research should combine self-report and objective data to examine associations with specific sedentary behaviours in the contexts within which they occur, as well as total sedentary time

    Moving through Motherhood:Involving the Public in Research to Inform Physical Activity Promotion throughout Pregnancy and Beyond

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    open access articleInformation received by women regarding physical activity during and after pregnancy often lacks clarity and may be conflicting and confusing. Without clear, engaging, accessible guidance centred on the experiences of pregnancy and parenting, the benefits of physical activity can be lost. We describe a collaborative process to inform the design of evidence-based, user-centred physical activity resources which reflect diverse experiences of pregnancy and early parenthood. Two iterative, collaborative phases involving patient and public involvement (PPI) workshops, a scoping survey (n = 553) and stakeholder events engaged women and maternity, policy and physical activity stakeholders to inform pilot resource development. These activities shaped understanding of challenges experienced by maternity and physical activity service providers, pregnant women and new mothers in relation to supporting physical activity. Working collaboratively with women and stakeholders, we co-designed pilot resources and identified important considerations for future resource development. Outcomes and lessons learned from this process will inform further work to support physical activity during pregnancy and beyond, but also wider health research where such collaborative approaches are important. We hope that drawing on our experiences and sharing outcomes from this work provide useful information for researchers, healthcare professionals, policy makers and those involved in supporting physical activity behaviour

    Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

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    Background and Aims: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers.Methods: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours.Results: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7h sleeping, 10.4h sedentary, 3.1h standing, 1.5h LIPA, and 1.3h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30min of SB, sleep, standing, or LIPA with MVPA was associated with-0.63 (95% confidence interval-0.48,-0.79),-0.43 (-0.25,-0.59),-0.40 (-0.25,-0.56), and-0.15 (0.05,-0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. Conclusions: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.</p

    Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

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    BACKGROUND AND AIMS: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers. METHODS: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours. RESULTS: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. CONCLUSIONS: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity

    Moving through Motherhood: Involving the Public in Research to Inform Physical Activity Promotion throughout Pregnancy and Beyond.

    Get PDF
    Information received by women regarding physical activity during and after pregnancy often lacks clarity and may be conflicting and confusing. Without clear, engaging, accessible guidance centred on the experiences of pregnancy and parenting, the benefits of physical activity can be lost. We describe a collaborative process to inform the design of evidence-based, user-centred physical activity resources which reflect diverse experiences of pregnancy and early parenthood. Two iterative, collaborative phases involving patient and public involvement (PPI) workshops, a scoping survey (n = 553) and stakeholder events engaged women and maternity, policy and physical activity stakeholders to inform pilot resource development. These activities shaped understanding of challenges experienced by maternity and physical activity service providers, pregnant women and new mothers in relation to supporting physical activity. Working collaboratively with women and stakeholders, we co-designed pilot resources and identified important considerations for future resource development. Outcomes and lessons learned from this process will inform further work to support physical activity during pregnancy and beyond, but also wider health research where such collaborative approaches are important. We hope that drawing on our experiences and sharing outcomes from this work provide useful information for researchers, healthcare professionals, policy makers and those involved in supporting physical activity behaviour

    Actigraph Accelerometer-Defined Boundaries for Sedentary Behaviour and Physical Activity Intensities in 7 Year Old Children

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    Background: Accurate objective assessment of sedentary and physical activity behaviours during childhood is integral to the understanding of their relation to later health outcomes, as well as to documenting the frequency and distribution of physical activity within a population.Purpose: To calibrate the Actigraph GT1M accelerometer, using energy expenditure (EE) as the criterion measure, to define thresholds for sedentary behaviour and physical activity categories suitable for use in a large scale epidemiological study in young children.Methods: Accelerometer-based assessments of physical activity (counts per minute) were calibrated against EE measures (kcal.kg(-1).hr(-1)) obtained over a range of exercise intensities using a COSMED K4b(2) portable metabolic unit in 53 seven-year-old children. Children performed seven activities: lying down viewing television, sitting upright playing a computer game, slow walking, brisk walking, jogging, hopscotch and basketball. Threshold count values were established to identify sedentary behaviour and light, moderate and vigorous physical activity using linear discriminant analysis (LDA) and evaluated using receiver operating characteristic (ROC) curve analysis.Results: EE was significantly associated with counts for all non-sedentary activities with the exception of jogging. Threshold values for accelerometer counts (counts. minute(-1)) were = 3841 for light, moderate and vigorous physical activity respectively. The area under the ROC curves for discrimination of sedentary behaviour and vigorous activity were 0.98. Boundaries for light and moderate physical activity were less well defined (0.61 and 0.60 respectively). Sensitivity and specificity were higher for sedentary (99% and 97%) and vigorous (95% and 91%) than for light (60% and 83%) and moderate (61% and 76%) thresholds.Conclusion: The accelerometer cut points established in this study can be used to classify sedentary behaviour and to distinguish between light, moderate and vigorous physical activity in children of this age

    A three arm cluster randomised controlled trial to test the effectiveness and cost-effectiveness of the SMART work & life intervention for reducing daily sitting time in office workers : study protocol

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    Background:Office-based workers typically spend 70-85% of working hours, and a large proportion of leisure time, sitting. High levels of sitting have been linked to poor health. There is a need for fully powered randomised controlled trials (RCTs) with long-term follow-up to test the effectiveness of interventions to reduce sitting. This paper describes the methodology of a three-arm cluster RCT designed to determine the effectiveness and cost-effectiveness of the SMART Work &amp; Life intervention, delivered with and without a height-adjustable desk, for reducing daily sitting. Methods/Design:A three-arm cluster RCT of 33 clusters (660 council workers) will be conducted in three areas in England (Leicester; Manchester; Liverpool). Office groups (clusters) will be randomised to the SMART Work &amp; Life intervention delivered with (group 1) or without (group 2) a height-adjustable desk or a control group (group 3). SMART Work &amp; Life includes organisational (e.g., management buy-in, provision/support for standing meetings), environmental (e.g., relocating waste bins, printers), and group/individual (education, action planning, goal setting, addressing barriers, coaching, self-monitoring, social support) level behaviour change strategies, with strategies driven by workplace champions. Baseline, 3, 12 and 24 month measures will be taken. Objectively measured daily sitting time (activPAL3). objectively measured sitting, standing, stepping, prolonged sitting and moderate-to-vigorous physical activity time and number of steps at work and daily; objectively measured sleep (wrist accelerometry). Adiposity, blood pressure, fasting glucose, glycated haemoglobin, cholesterol (total, HDL, LDL) and triglycerides will be assessed from capillary blood samples. Questionnaires will examine dietary intake, fatigue, musculoskeletal issues, job performance and satisfaction, work engagement, occupational and general fatigue, stress, presenteeism, anxiety and depression and sickness absence (organisational records). Quality of life and resources used (e.g. GP visits, outpatient attendances) will also be assessed. We will conduct a full process evaluation and cost-effectiveness analysis. Discussion:The results of this RCT will 1) help to understand how effective an important simple, yet relatively expensive environmental change is for reducing sitting, 2) provide evidence on changing behaviour across all waking hours, and 3) provide evidence for policy guidelines around population and workplace health and well-being. Trial registration: ISRCTN11618007 . Registered on 21 January 2018

    The SOS-framework (Systems of Sedentary behaviours): an international transdisciplinary consensus framework for the study of determinants, research priorities and policy on sedentary behaviour across the life course: a DEDIPAC-study.

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    BACKGROUND: Ecological models are currently the most used approaches to classify and conceptualise determinants of sedentary behaviour, but these approaches are limited in their ability to capture the complexity of and interplay between determinants. The aim of the project described here was to develop a transdisciplinary dynamic framework, grounded in a system-based approach, for research on determinants of sedentary behaviour across the life span and intervention and policy planning and evaluation. METHODS: A comprehensive concept mapping approach was used to develop the Systems Of Sedentary behaviours (SOS) framework, involving four main phases: (1) preparation, (2) generation of statements, (3) structuring (sorting and ranking), and (4) analysis and interpretation. The first two phases were undertaken between December 2013 and February 2015 by the DEDIPAC KH team (DEterminants of DIet and Physical Activity Knowledge Hub). The last two phases were completed during a two-day consensus meeting in June 2015. RESULTS: During the first phase, 550 factors regarding sedentary behaviour were listed across three age groups (i.e., youths, adults and older adults), which were reduced to a final list of 190 life course factors in phase 2 used during the consensus meeting. In total, 69 international delegates, seven invited experts and one concept mapping consultant attended the consensus meeting. The final framework obtained during that meeting consisted of six clusters of determinants: Physical Health and Wellbeing (71% consensus), Social and Cultural Context (59% consensus), Built and Natural Environment (65% consensus), Psychology and Behaviour (80% consensus), Politics and Economics (78% consensus), and Institutional and Home Settings (78% consensus). Conducting studies on Institutional Settings was ranked as the first research priority. The view that this framework captures a system-based map of determinants of sedentary behaviour was expressed by 89% of the participants. CONCLUSION: Through an international transdisciplinary consensus process, the SOS framework was developed for the determinants of sedentary behaviour through the life course. Investigating the influence of Institutional and Home Settings was deemed to be the most important area of research to focus on at present and potentially the most modifiable. The SOS framework can be used as an important tool to prioritise future research and to develop policies to reduce sedentary time
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