Seasonal variations in lifestyle behaviours and their relationship with indicators for poor health

The increasing evidence of associations between physical activity, sedentary behaviour, sleep duration and diet and both immediate and long term health implications is of public health concern. There is a need to further our understanding of the patterns of these behaviours and how they affect poor health indicators individually and simultaneously. This thesis aims to advance the current literature by investigating associations between multiple lifestyle behaviours and indicators for poor health and identifying patterns of physical activity, sedentary behaviour, sleep duration and dietary intake. Anthropometric measurements and bioelectrical impedance analysis were collected from 72 UK adults. These participants were asked to wear an ActiGraph GT1M accelerometer to objectively measure their physical activity and sedentary behaviour across 7 consecutive days. Over these 7 days, participants also completed a self-report daily sleep diary and a food frequency questionnaire. Participants were asked to complete these measurements at 4 different time points across the year in order to capture these behaviours over each season; 46 participants completed all 4 seasons. Using the data collected from the 72 participants who completed at least 1 season, regression analyses were conducted to identify associations between lifestyle behaviours and indicators for poor health. Repeated measures ANOVAs were conducted on data from 52 participants who provided the full 7 days of data during their initial measurement period to assess day of the week variations in physical activity, sedentary behaviour and sleep patterns. Repeated measures ANOVAs were also conducted on physical activity, sedentary behaviour, sleep and dietary intake data provided by the 46 participants who provided 4 seasons of data to assess seasonal variation. This thesis demonstrated that in a sample of relatively active, UK adults, time spent in moderate-vigorous physical activity and sedentary behaviour had a negative association with BMI and body fat percentage, increased time spent in moderate-vigorous physical activity was also associated with decreases in waist circumference. Light intensity physical activity had a positive association with BMI, body fat percentage and diastolic blood pressure. There were significant day of the week variations in light intensity physical activity, sedentary behaviour and time spent in bed, with light intensity physical activity and time in bed being significantly higher on a Sunday, whilst sedentary behaviour was significantly lower on a Sunday in this sample of UK adults. In addition to day of the week variations, there were seasonal variations in light intensity physical activity, sedentary behaviour and time spent in bed and sleep durations (weekdays only). Over the winter months, light intensity physical activity was significantly lower, whilst sedentary behaviour, time in bed and total sleep time was significantly higher. No seasonal variations in time spent in moderate-vigorous intensity physical activity or diet were observed in the present sample. This thesis demonstrates that lifestyle behaviours that have been found to affect health do vary over the week and across different seasons. This research has implications for surveillance studies which estimate these behaviours at one time point throughout the year, and also for interventions aimed at improving these behaviours which are implemented at just one time period of the year. Strategies for overcoming barriers to PA under unfavourable environmental conditions will be needed for this to be achieved, in addition to interventions reducing SB, even in the winter months

Office workers' objectively measured sedentary behavior and physical activity during and outside working hours

OBJECTIVE: To examine objectively determined sedentary behavior and physical activity (PA) during and outside working hours in full-time office workers. METHODS: A total of 170 participants wore an ActiGraph GT1M accelerometer for 7 days. Time spent sedentary (<100 counts/min), in light-intensity PA (100 to 1951 counts/min), and moderate-to-vigorous PA (≥1952 counts/min) was calculated for workdays (including working hours and nonworking hours) and nonworkdays. RESULTS: Participants accumulated significantly higher levels of sedentary behavior (68% vs 60%) and lower levels of light-intensity activity (28% vs 36%) on workdays in comparison with nonworkdays. Up to 71% of working hours were spent sedentary. Individuals who were most sedentary at work were also more sedentary outside work. CONCLUSIONS: Those who are most sedentary at work do not compensate by increasing their PA or reducing their sedentary time outside work. Occupational interventions should address workplace and leisure-time sedentary behavior

Evaluation of a commercially available pedometer used to promote physical activity as part of a national programme

Objective: To assess the accuracy of a pedometer (manufactured by Silva) currently being used as part of a national programme to promote physical activity in the UK. Methods: Laboratory study: 68 participants (age 19.2±2.7 years, BMI 22.5±3.3 kg/m2) wore 2 Silva pedometers (over the right and left hips) whilst walking on a motorised treadmill at 2, 2.5, 3, 3.5 and 4mph. Pedometer step counts were compared with actual steps counted. Free-living study: 134 participants (age 36.4±18.1 years, BMI 26.3±5.1 kg/m2) wore one Silva pedometer, one New-Lifestyles NL-1000 pedometer and an ActiGraph GT1M accelerometer (the criterion) during waking hours for one day. Step counts registered by the Silva and NL- 1000 pedometers were compared to ActiGraph step counts. Percent error of the pedometers were compared across normal-weight (n=58), overweight (n=45) and obese (n=31) participants. Results: Laboratory study: Across the speeds tested percent error in steps ranged from 6.7 (4mph) – 46.9% (2mph). Free-living study: Overall percent errors of the Silva and NL-1000 pedometers relative to the criterion were 36.3% and 9% respectively. Significant differences in percent error of the Silva pedometer were observed across BMI groups (normal-weight 21%, overweight 40.2%, obese 59.2%, P<0.001). Conclusion: The findings suggest the Silva pedometer is unacceptably inaccurate for activity promotion purposes particularly in overweight and obese adults. Pedometers are an excellent tool for activity promotion however the use of inexpensive, untested pedometers is not recommended as they will lead to user frustration, low intervention compliance, and adverse reaction to the instrument, potentially impacting future public health campaigns

Stand More AT Work (SMArT Work): using the behaviour change wheel to develop an intervention to reduce sitting time in the workplace

Background: Sitting (sedentary behaviour) is widespread among desk-based office workers and a high level of sedentary behaviour is a risk factor for poor health. Reducing workplace sitting time is therefore an important prevention strategy. Interventions are more likely to be effective if they are theory and evidence-based. The Behaviour Change Wheel (BCW) provides a framework for intervention development. This article describes the development of the Stand More AT Work (SMArT Work) intervention, which aims to reduce sitting time among National Health Service (NHS) office-based workers in Leicester, UK. Methods: We followed the BCW guide and used the Capability, Opportunity and Motivation Behaviour (COM-B) model to conduct focus group discussions with 39 NHS office workers. With these data we used the taxonomy of Behaviour Change Techniques (BCTv1) to identify the most appropriate strategies for facilitating behaviour change in our intervention. To identify the best method for participants to self-monitor their sitting time, a sub-group of participants (n = 31) tested a number of electronic self-monitoring devices. Results: From our BCW steps and the BCT-Taxonomy we identified 10 behaviour change strategies addressing environmental (e.g. provision of height adjustable desks,), organisational (e.g. senior management support, seminar), and individual level (e.g. face-to-face coaching session) barriers. The Darma cushion scored the highest for practicality and acceptability for self-monitoring sitting. Conclusion: The BCW guide, COM-B model and BCT-Taxonomy can be applied successfully in the context of designing a workplace intervention for reducing sitting time through standing and moving more. The intervention was developed in collaboration with office workers (a participatory approach) to ensure relevance for them and their work situation. The effectiveness of this intervention is currently being evaluated in a randomised controlled trial

SMArT Work: Stand more at Work: The development of behaviour changes strategies for increasing standing and movement among sedentary office workers

SMArT Work: Stand more at Work: The development of behaviour changes strategies for increasing standing and movement among sedentary office worker

Providing NHS staff with height-adjustable workstations and behaviour change strategies to reduce workplace sitting time: protocol for the Stand More AT (SMArT) Work cluster randomised controlled trial

BACKGROUND. High levels of sedentary behaviour (i.e., sitting) are a risk factor for poor health. With high levels of sitting widespread in desk-based office workers, office workplaces are an appropriate setting for interventions aimed at reducing sedentary behaviour. This paper describes the development processes and proposed intervention procedures of Stand More AT (SMArT) Work, a multi-component randomised control (RCT) trial which aims to reduce occupational sitting time in desk-based office workers within the National Health Service (NHS). METHODS/DESIGN. SMArT Work consists of 2 phases: 1) intervention development: The development of the SMArT Work intervention takes a community-based participatory research approach using the Behaviour Change Wheel. Focus groups will collect detailed information to gain a better understanding of the most appropriate strategies, to sit alongside the provision of height-adjustable workstations, at the environmental, organisational and individual level that support less occupational sitting. 2) intervention delivery and evaluation: The 12 month cluster RCT aims to reduce workplace sitting in the University Hospitals of Leicester NHS Trust. Desk-based office workers (n = 238) will be randomised to control or intervention clusters, with the intervention group receiving height-adjustable workstations and supporting techniques based on the feedback received from the development phase. Data will be collected at four time points; baseline, 3, 6 and 12 months. The primary outcome is a reduction in sitting time, measured by the activPALTM micro at 12 months. Secondary outcomes include objectively measured physical activity and a variety of work-related health and psycho-social measures. A process evaluation will also take place. DISCUSSION. This study will be the first long-term, evidence-based, multi-component cluster RCT aimed at reducing occupational sitting within the NHS. This study will help form a better understanding and knowledge base of facilitators and barriers to creating a healthier work environment and contribute to health and wellbeing policy. TRIAL REGISTRATION. ISRCTN10967042. Registered 2 February 2015

Seasonal variation in physical activity, sedentary behaviour and sleep in a sample of UK adults

Background: Physical activity (PA), sedentary behaviour (SB), sleep and diet have all been associated with increased risk for chronic disease. Seasonality is often overlooked as a determinant of these behaviours in adults. Currently, no study has simultaneously monitored these behaviours in UK adults to assess seasonal variation. Aim: The present study investigated whether PA, SB, sleep and diet differed over season in UK adults. Subjects and methods: Forty-six adults (72% female; age = 41.7 ± 14.4 years, BMI = 24.9 ± 4.4 kg/m2) completed four 7-day monitoring periods; one during each season of the year. The ActiGraph GT1M was used to monitor PA and SB. Daily sleep diaries monitored time spent in bed (TIB) and total sleep time (TST). The European Prospective Investigation of Cancer (EPIC) food frequency questionnaire (FFQ) assessed diet. Repeated measures ANOVAs were used to identify seasonal differences in behaviours. Results: Light-intensity PA was significantly higher in summer and spring (p  0.05). Conclusions: Findings support the concept that health promotion campaigns need to encourage year-round participation in light intensity PA, whilst limiting SB, particularly during the winter months