1
|
Sansom K, Reynolds A, Windred D, Phillips A, Dhaliwal SS, Walsh J, Maddison K, Singh B, Eastwood P, McArdle N. The interrelationships between sleep regularity, obstructive sleep apnea, and hypertension in a middle-aged community population. Sleep 2024; 47:zsae001. [PMID: 38180870 PMCID: PMC10925954 DOI: 10.1093/sleep/zsae001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 12/20/2023] [Indexed: 01/07/2024] Open
Abstract
STUDY OBJECTIVES Little is known about the interrelationships between sleep regularity, obstructive sleep apnea (OSA) and important health markers. This study examined whether irregular sleep is associated with OSA and hypertension, and if this modifies the known association between OSA and hypertension. METHODS Six hundred and two adults (age mean(SD) = 56.96(5.51) years, female = 60%) from the Raine Study who were not evening or night shift workers were assessed for OSA (in-laboratory polysomnography; apnea-hypopnea index ≥ 15 events/hour), hypertension (doctor diagnosed, or systolic blood pressure ≥140 mmHg and/or diastolic ≥90 mmHg) and sleep (wrist actigraphy for ≥5 days). A sleep regularity index (SRI) was determined from actigraphy. Participants were categorized by tertiles as severely irregular, mildly irregular, or regular sleepers. Logistic regression models examined the interrelationships between SRI, OSA and hypertension. Covariates included age, sex, body mass index, actigraphy sleep duration, insomnia, depression, activity, alcohol, smoking, and antihypertensive medication. RESULTS Compared to regular sleepers, participants with mildly irregular (OR 1.97, 95% confidence intervals [CI] 1.20 to 3.27) and severely irregular (OR 2.06, 95% CI: 1.25 to 3.42) sleep had greater odds of OSA. Compared to those with no OSA and regular sleep, OSA and severely irregular sleep combined had the highest odds of hypertension (OR 2.34 95% CI: 1.07 to 5.12; p for interaction = 0.02) while those with OSA and regular/mildly irregular sleep were not at increased risk (p for interaction = 0.20). CONCLUSIONS Sleep irregularity may be an important modifiable target for hypertension among those with OSA.
Collapse
Affiliation(s)
- Kelly Sansom
- Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
- Queen Elizabeth II Medical Centre, West Australian Sleep Disorders Research Institute, Nedlands, WA, Australia
- Flinders University, College of Medicine and Public Health, Flinders Health and Medical Research Institute - Sleep Health, Adelaide, SA, Australia
| | - Amy Reynolds
- Flinders University, College of Medicine and Public Health, Flinders Health and Medical Research Institute - Sleep Health, Adelaide, SA, Australia
| | - Daniel Windred
- School of Psychological Sciences, Monash University, Turner Institute for Brain and Mental Health, Clayton, VIC, Australia
| | - Andrew Phillips
- School of Psychological Sciences, Monash University, Turner Institute for Brain and Mental Health, Clayton, VIC, Australia
| | - Satvinder S Dhaliwal
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Office of the Provost, Singapore University of Social Sciences, Clementi, Singapore
- Duke-NUS Medical School, National University of Singapore, Singapore
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Pulau Pinang, Malaysia
| | - Jennifer Walsh
- Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
- Queen Elizabeth II Medical Centre, West Australian Sleep Disorders Research Institute, Nedlands, WA, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
| | - Kathleen Maddison
- Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
- Queen Elizabeth II Medical Centre, West Australian Sleep Disorders Research Institute, Nedlands, WA, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
| | - Bhajan Singh
- Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
- Queen Elizabeth II Medical Centre, West Australian Sleep Disorders Research Institute, Nedlands, WA, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
| | - Peter Eastwood
- Health Futures Institute, Murdoch University, Perth, WA, Australia
| | - Nigel McArdle
- Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
- Queen Elizabeth II Medical Centre, West Australian Sleep Disorders Research Institute, Nedlands, WA, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
| |
Collapse
|
2
|
Harris R, Beatty CJ, Cori JM, Spitz G, Soleimanloo SS, Peterson SA, Naqvi A, Barnes M, Downey LA, Shiferaw BA, Anderson C, Tucker AJ, Clark A, Rajaratnam SMW, Howard ME, Sletten TL, Wolkow AP. The impact of break duration, time of break onset, and prior shift duration on the amount of sleep between shifts in heavy vehicle drivers. J Sleep Res 2023; 32:e13730. [PMID: 36193767 DOI: 10.1111/jsr.13730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/16/2022] [Accepted: 08/31/2022] [Indexed: 11/28/2022]
Abstract
This study aimed to examine the impact of break duration between consecutive shifts, time of break onset, and prior shift duration on total sleep time (TST) between shifts in heavy vehicle drivers (HVDs), and to assess the interaction between break duration and time of break onset. The sleep (actigraphy and sleep diaries) and work shifts (work diaries) of 27 HVDs were monitored during their usual work schedule for up to 9 weeks. Differences in TST between consecutive shifts and days off were assessed. Linear mixed models (followed by pairwise comparisons) assessed whether break duration, prior shift duration, time of break onset, and the interaction between break duration and break onset were related to TST between shifts. Investigators found TST between consecutive shifts (mean [SD] 6.38 [1.38] h) was significantly less than on days off (mean [SD] 7.63 [1.93] h; p < 0.001). Breaks starting between 12:01 and 8:00 a.m. led to shorter sleep (p < 0.05) compared to breaks starting between 4:01 and 8:00 p.m. Break durations up to 7, 9, and 11 h (Australian and European minimum break durations) resulted in a mean (SD) of 4.76 (1.06), 5.66 (0.77), and 6.41 (1.06) h of sleep, respectively. The impact of shift duration prior to the break and the interaction between break duration and time of break were not significant. HVDs' sleep between workdays is influenced independently by break duration and time of break onset. This naturalistic study provides evidence that current break regulations prevent sufficient sleep duration in this industry. Work regulations should evaluate appropriate break durations and break onset times to allow longer sleep opportunities for HVDs.
Collapse
Affiliation(s)
- Rachael Harris
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Caroline J Beatty
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia.,Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia.,Department of Respiratory and Sleep Medicine, Austin Health, Heidelberg, Victoria, Australia
| | - Jennifer M Cori
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia.,Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia.,Department of Respiratory and Sleep Medicine, Austin Health, Heidelberg, Victoria, Australia
| | - Gershon Spitz
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Shamsi Shekari Soleimanloo
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia.,Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia.,Department of Respiratory and Sleep Medicine, Austin Health, Heidelberg, Victoria, Australia.,Institute for Social Science Research, The University of Queensland, Brisbane, Queensland, Australia
| | - Scott A Peterson
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia
| | - Aqsa Naqvi
- Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia.,Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia.,Department of Respiratory and Sleep Medicine, Austin Health, Heidelberg, Victoria, Australia
| | - Maree Barnes
- Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia.,Department of Respiratory and Sleep Medicine, Austin Health, Heidelberg, Victoria, Australia.,Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
| | - Luke A Downey
- Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia.,Centre for Human Psychopharmacology, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Brook A Shiferaw
- Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia.,Centre for Human Psychopharmacology, Swinburne University of Technology, Hawthorn, Victoria, Australia.,Seeing Machines Ltd., Fyshwick, Australian Capital Territory, Australia
| | - Clare Anderson
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia
| | - Andrew J Tucker
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia
| | - Anna Clark
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia
| | - Shantha M W Rajaratnam
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia
| | - Mark E Howard
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia.,Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia.,Department of Respiratory and Sleep Medicine, Austin Health, Heidelberg, Victoria, Australia.,Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
| | - Tracey L Sletten
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia
| | - Alexander P Wolkow
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Victoria, Australia
| | | |
Collapse
|
3
|
Ruettger K, Clemes SA, Chen YL, Edwardson CL, Guest A, Gilson ND, Gray LJ, Johnson V, Paine NJ, Sherry AP, Sayyah M, Troughton J, Varela-Mato V, Yates T, King JA. Drivers with and without Obesity Respond Differently to a Multi-Component Health Intervention in Heavy Goods Vehicle Drivers. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15546. [PMID: 36497618 PMCID: PMC9739045 DOI: 10.3390/ijerph192315546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/14/2022] [Accepted: 11/17/2022] [Indexed: 06/17/2023]
Abstract
Physical inactivity and obesity are widely prevalent in Heavy Goods Vehicle (HGV) drivers. We analysed whether obesity classification influenced the effectiveness of a bespoke structured lifestyle intervention ('SHIFT') for HGV drivers. The SHIFT programme was evaluated within a cluster randomised controlled trial, across 25 transport depots in the UK. After baseline assessments, participants within intervention sites received a 6-month multi-component health behaviour change intervention. Intervention responses (verses control) were stratified by obesity status (BMI < 30 kg/m2, n = 131; BMI ≥ 30 kg/m2, n = 113) and compared using generalised estimating equations. At 6-months, favourable differences were found in daily steps (adjusted mean difference 1827 steps/day, p < 0.001) and sedentary time (adjusted mean difference -57 min/day, p < 0.001) in drivers with obesity undertaking the intervention, relative to controls with obesity. Similarly, in drivers with obesity, the intervention reduced body weight (adjusted mean difference -2.37 kg, p = 0.002) and led to other favourable anthropometric outcomes, verses controls with obesity. Intervention effects were absent for drivers without obesity, and for all drivers at 16-18-months follow-up. Obesity classification influenced HGV drivers' behavioural responses to a multi-component health-behaviour change intervention. Therefore, the most at-risk commercial drivers appear receptive to a health promotion programme.
Collapse
Affiliation(s)
- Katharina Ruettger
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
| | - Stacy A. Clemes
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
| | - Yu-Ling Chen
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
| | - Charlotte L. Edwardson
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester LE5 4PW, UK
| | - Amber Guest
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
| | - Nicholas D. Gilson
- School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane 4072, Australia
| | - Laura J. Gray
- Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - Vicki Johnson
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester General Hospital, Leicester LE5 4PW, UK
| | - Nicola J. Paine
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
| | - Aron P. Sherry
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
| | - Mohsen Sayyah
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
| | - Jacqui Troughton
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester General Hospital, Leicester LE5 4PW, UK
| | - Veronica Varela-Mato
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
| | - Thomas Yates
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester LE5 4PW, UK
| | - James A. King
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
| |
Collapse
|
4
|
Clemes SA, Varela-Mato V, Bodicoat DH, Brookes CL, Chen YL, Cox E, Edwardson CL, Gray LJ, Guest A, Johnson V, Munir F, Paine NJ, Richardson G, Ruettger K, Sayyah M, Sherry A, Paola ASD, Troughton J, Walker S, Yates T, King J. A multicomponent structured health behaviour intervention to improve physical activity in long-distance HGV drivers: the SHIFT cluster RCT. PUBLIC HEALTH RESEARCH 2022. [DOI: 10.3310/pnoy9785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Background
Long-distance heavy goods vehicle drivers are exposed to a multitude of risk factors associated with their occupation. The working environment of heavy goods vehicle drivers provides limited opportunities for a healthy lifestyle, and, consequently, heavy goods vehicle drivers exhibit higher than nationally representative rates of obesity and obesity-related comorbidities, and are underserved in terms of health promotion initiatives.
Objective
The aim of this trial was to test the effectiveness and cost-effectiveness of the multicomponent Structured Health Intervention For Truckers (SHIFT) programme, compared with usual care, at both 6 months and 16–18 months.
Design
A two-arm cluster randomised controlled trial, including a cost-effectiveness analysis and process evaluation.
Setting
Transport depots throughout the Midlands region of the UK.
Participants
Heavy goods vehicle drivers.
Intervention
The 6-month SHIFT programme included a group-based interactive 6-hour education session, health coach support and equipment provision [including a Fitbit® (Fitbit Inc., San Francisco, CA, US) and resistance bands/balls to facilitate a ‘cab workout’]. Clusters were randomised following baseline measurements to either the SHIFT arm or the control arm.
Main outcome measures
Outcome measures were assessed at baseline, with follow-up assessments occurring at both 6 months and 16–18 months. The primary outcome was device-measured physical activity, expressed as mean steps per day, at 6-month follow-up. Secondary outcomes included device-measured sitting, standing, stepping, physical activity and sleep time (on any day, workdays and non-workdays), along with adiposity, biochemical measures, diet, blood pressure, psychophysiological reactivity, cognitive function, functional fitness, mental well-being, musculoskeletal symptoms and work-related psychosocial variables. Cost-effectiveness and process evaluation data were collected.
Results
A total of 382 participants (mean ± standard deviation age: 48.4 ± 9.4 years; mean ± standard deviation body mass index: 30.4 kg/m2 ± 5.1 kg/m2; 99% male) were recruited across 25 clusters. Participants were randomised (at the cluster level) to either the SHIFT arm (12 clusters, n = 183) or the control arm (13 clusters, n = 199). At 6 months, 209 (54.7%) participants provided primary outcome data. Significant differences in mean daily steps were found between arms, with participants in the SHIFT arm accumulating 1008 more steps per day than participants in the control arm (95% confidence interval 145 to 1871 steps; p = 0.022), which was largely driven by the maintenance of physical activity levels in the SHIFT arm and a decline in physical activity levels in the control arm. Favourable differences at 6 months were also seen in the SHIFT arm, relative to the control arm, in time spent sitting, standing and stepping, and time in moderate or vigorous activity. No differences between arms were observed at 16–18 months’ follow-up. No differences were observed between arms in the other secondary outcomes at either follow-up (i.e. 6 months and 16–18 months). The process evaluation demonstrated that the intervention was well received by participants and that the intervention reportedly had a positive impact on their health behaviours. The average total cost of delivering the SHIFT programme was £369.57 per driver, and resulting quality-adjusted life-years were similar across trial arms (SHIFT arm: 1.22, 95% confidence interval 1.19 to 1.25; control arm: 1.25, 95% confidence interval 1.22 to 1.27).
Limitations
A higher (31.4%) than anticipated loss to follow-up was experienced at 6 months, with fewer (54.7%) participants providing valid primary outcome data at 6 months. The COVID-19 pandemic presents a major confounding factor, which limits our ability to draw firm conclusions regarding the sustainability of the SHIFT programme.
Conclusion
The SHIFT programme had a degree of success in positively impacting physical activity levels and reducing sitting time in heavy goods vehicle drivers at 6-months; however, these differences were not maintained at 16–18 months.
Future work
Further work involving stakeholder engagement is needed to refine the content of the programme, based on current findings, followed by the translation of the SHIFT programme into a scalable driver training resource.
Trial registration
This trial is registered as ISRCTN10483894.
Funding
This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 10, No. 12. See the NIHR Journals Library website for further project information.
Collapse
Affiliation(s)
- Stacy A Clemes
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
| | - Veronica Varela-Mato
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
| | | | | | - Yu-Ling Chen
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
| | - Edward Cox
- Centre for Health Economics, University of York, York, UK
| | - Charlotte L Edwardson
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Laura J Gray
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Amber Guest
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Vicki Johnson
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Fehmidah Munir
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
| | - Nicola J Paine
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
| | | | - Katharina Ruettger
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Mohsen Sayyah
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Aron Sherry
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
| | | | - Jacqui Troughton
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Simon Walker
- Centre for Health Economics, University of York, York, UK
| | - Thomas Yates
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - James King
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Leicester, UK
| |
Collapse
|
5
|
Clemes SA, Varela-Mato V, Bodicoat DH, Brookes CL, Chen YL, Edwardson CL, Gray LJ, Guest AJ, Johnson V, Munir F, Paine NJ, Richardson G, Ruettger K, Sayyah M, Sherry A, Di Paola AS, Troughton J, Yates T, King JA. The effectiveness of the Structured Health Intervention For Truckers (SHIFT): a cluster randomised controlled trial (RCT). BMC Med 2022; 20:195. [PMID: 35606763 PMCID: PMC9126630 DOI: 10.1186/s12916-022-02372-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 04/11/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Long distance heavy goods vehicle (HGV) drivers exhibit higher than nationally representative rates of obesity, and obesity-related co-morbidities, and are underserved in terms of health promotion initiatives. The purpose of this study was to evaluate the effectiveness of the multicomponent 'Structured Health Intervention For Truckers' (SHIFT), compared to usual care, at 6- and 16-18-month follow-up. METHODS We conducted a two-arm cluster RCT in transport sites throughout the Midlands, UK. Outcome measures were assessed at baseline, at 6- and 16-18-month follow-up. Clusters were randomised (1:1) following baseline measurements to either the SHIFT arm or usual practice control arm. The 6-month SHIFT programme included a group-based interactive 6-h education and behaviour change session, health coach support and equipment provision (Fitbit® and resistance bands/balls to facilitate a 'cab workout'). The primary outcome was device-assessed physical activity (mean steps/day) at 6 months. Secondary outcomes included the following: device-assessed sitting, physical activity intensity and sleep; cardiometabolic health, diet, mental wellbeing and work-related psychosocial variables. Data were analysed using mixed-effect linear regression models using a complete-case population. RESULTS Three hundred eighty-two HGV drivers (mean ± SD age: 48.4 ± 9.4 years, BMI: 30.4 ± 5.1 kg/m2, 99% male) were recruited across 25 clusters (sites) and randomised into either the SHIFT (12 clusters, n = 183) or control (13 clusters, n = 199) arms. At 6 months, 209 (55%) participants provided primary outcome data. Significant differences in mean daily steps were found between groups, in favour of the SHIFT arm (adjusted mean difference: 1008 steps/day, 95% CI: 145-1871, p = 0.022). Favourable differences were also seen in the SHIFT group, relative to the control group, in time spent sitting (- 24 mins/day, 95% CI: - 43 to - 6), and moderate-to-vigorous physical activity (6 mins/day, 95% CI: 0.3-11). Differences were not maintained at 16-18 months. No differences were observed between groups in the other secondary outcomes at either follow-up. CONCLUSIONS The SHIFT programme led to a potentially clinically meaningful difference in daily steps, between trial arms, at 6 months. Whilst the longer-term impact is unclear, the programme offers potential to be incorporated into driver training courses to promote activity in this at-risk, underserved and hard-to-reach essential occupational group. TRIAL REGISTRATION ISRCTN10483894 (date registered: 01/03/2017).
Collapse
Affiliation(s)
- Stacy A Clemes
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK. .,NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK.
| | - Veronica Varela-Mato
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK.,NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| | | | - Cassandra L Brookes
- Leicester Clinical Trials Unit, University of Leicester, Leicester, LE1 7RH, UK
| | - Yu-Ling Chen
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK.,NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| | - Charlotte L Edwardson
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK.,Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
| | - Laura J Gray
- Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Amber J Guest
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK
| | - Vicki Johnson
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, LE5 4PW, UK
| | - Fehmidah Munir
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK.,NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| | - Nicola J Paine
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK.,NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| | - Gerry Richardson
- Centre for Health Economics, University of York, York, YO10 5DD, UK
| | - Katharina Ruettger
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK
| | - Mohsen Sayyah
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK
| | - Aron Sherry
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK.,NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| | - Ana Suazo Di Paola
- Leicester Clinical Trials Unit, University of Leicester, Leicester, LE1 7RH, UK
| | - Jacqui Troughton
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, LE5 4PW, UK
| | - Thomas Yates
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK.,Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
| | - James A King
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK.,NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| |
Collapse
|
6
|
Relationship between Objectively and Subjectively Measured Physical Activity in Adolescents during and after COVID-19 Restrictions. Behav Sci (Basel) 2021; 11:bs11120177. [PMID: 34940112 PMCID: PMC8698612 DOI: 10.3390/bs11120177] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 12/03/2021] [Accepted: 12/08/2021] [Indexed: 11/24/2022] Open
Abstract
Background: Studying the relationship between subjectively and objectively measured physical activity (PA) can provide viable information on youths’ behaviors. However, the restrictions due to COVID-19 pandemic, which reduced children’s possibilities to be active, may negatively affect it. The aim of this study was to assess the relationship between subjectively and objectively measured PA levels (light, moderate, vigorous, and moderate-to-vigorous) during COVID-19-based restrictions and after they were lifted, and to determine whether such relationships changed in these two periods. Methods: A total of 26 adolescents (58% girls; mean age = 12.4 ± 0.5) wore accelerometers during public restrictions and after they were removed. Participants also completed the International Physical Activity Questionnaire during the same periods. Results: High significant correlations were found at all levels of PA (r = 0.767–0.968) in both time periods, except for moderate PA during restrictions. Comparing the two periods, significantly higher correlations were found for moderate PA (p < 0.001) and moderate-to-vigorous PA (p = 0.003) after restrictions were lifted. Conclusions: In this highly active cohort of adolescents, results emphasize the potential threat of lockdown conditions for youths’ ability to accurately perceive their behaviors, with possible detrimental consequences on the short- and long-term health.
Collapse
|