Behavioural interventions to promote physical activity in a multiethnic population at high risk of diabetes: PROPELS three-arm RCT.

BACKGROUND Type 2 diabetes is a leading cause of mortality globally and accounts for significant health resource expenditure. Increased physical activity can reduce the risk of diabetes. However, the longer-term clinical effectiveness and cost-effectiveness of physical activity interventions in those at high risk of type 2 diabetes is unknown. OBJECTIVES To investigate whether or not Walking Away from Diabetes (Walking Away) - a low-resource, 3-hour group-based behavioural intervention designed to promote physical activity through pedometer use in those with prediabetes - leads to sustained increases in physical activity when delivered with and without an integrated mobile health intervention compared with control. DESIGN Three-arm, parallel-group, pragmatic, superiority randomised controlled trial with follow-up conducted at 12 and 48 months. SETTING Primary care and the community. PARTICIPANTS Adults whose primary care record included a prediabetic blood glucose measurement recorded within the past 5 years [HbA1c ≥ 42 mmol/mol (6.0%), < 48 mmol/mol (6.5%) mmol/mol; fasting glucose ≥ 5.5 mmol/l, < 7.0 mmol/l; or 2-hour post-challenge glucose ≥ 7.8 mmol/l, < 11.1 mmol/l] were recruited between December 2013 and February 2015. Data collection was completed in July 2019. INTERVENTIONS Participants were randomised (1 : 1 : 1) using a web-based tool to (1) control (information leaflet), (2) Walking Away with annual group-based support or (3) Walking Away Plus (comprising Walking Away, annual group-based support and a mobile health intervention that provided automated, individually tailored text messages to prompt pedometer use and goal-setting and provide feedback, in addition to biannual telephone calls). Participants and data collectors were not blinded; however, the staff who processed the accelerometer data were blinded to allocation. MAIN OUTCOME MEASURES The primary outcome was accelerometer-measured ambulatory activity (steps per day) at 48 months. Other objective and self-reported measures of physical activity were also assessed. RESULTS A total of 1366 individuals were randomised (median age 61 years, median body mass index 28.4 kg/m2, median ambulatory activity 6638 steps per day, women 49%, black and minority ethnicity 28%). Accelerometer data were available for 1017 (74%) and 993 (73%) individuals at 12 and 48 months, respectively. The primary outcome assessment at 48 months found no differences in ambulatory activity compared with control in either group (Walking Away Plus: 121 steps per day, 97.5% confidence interval -290 to 532 steps per day; Walking Away: 91 steps per day, 97.5% confidence interval -282 to 463). This was consistent across ethnic groups. At the intermediate 12-month assessment, the Walking Away Plus group had increased their ambulatory activity by 547 (97.5% confidence interval 211 to 882) steps per day compared with control and were 1.61 (97.5% confidence interval 1.05 to 2.45) times more likely to achieve 150 minutes per week of objectively assessed unbouted moderate to vigorous physical activity. In the Walking Away group, there were no differences compared with control at 12 months. Secondary anthropometric, biomechanical and mental health outcomes were unaltered in either intervention study arm compared with control at 12 or 48 months, with the exception of small, but sustained, reductions in body weight in the Walking Away study arm (≈ 1 kg) at the 12- and 48-month follow-ups. Lifetime cost-effectiveness modelling suggested that usual care had the highest probability of being cost-effective at a threshold of £20,000 per quality-adjusted life-year. Of 50 serious adverse events, only one (myocardial infarction) was deemed possibly related to the intervention and led to the withdrawal of the participant from the study. LIMITATIONS Loss to follow-up, although the results were unaltered when missing data were replaced using multiple imputation. CONCLUSIONS Combining a physical activity intervention with text messaging and telephone support resulted in modest, but clinically meaningful, changes in physical activity at 12 months, but the changes were not sustained at 48 months. FUTURE WORK Future research is needed to investigate which intervention types, components and features can help to maintain physical activity behaviour change over the longer term. TRIAL REGISTRATION Current Controlled Trials ISRCTN83465245. FUNDING This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 77. See the NIHR Journals Library website for further project information.

[1]  K. Khunti,et al.  Promoting physical activity in a multi-ethnic population at high risk of diabetes: the 48-month PROPELS randomised controlled trial , 2021, BMC Medicine.

[2]  K. Khunti,et al.  Distal technology interventions in people with diabetes: an umbrella review of multiple health outcomes , 2020, Diabetic medicine : a journal of the British Diabetic Association.

[3]  M. Davies,et al.  Wrist-worn accelerometers: recommending ~1.0 mg as the minimum clinically important difference (MCID) in daily average acceleration for inactive adults , 2020, British Journal of Sports Medicine.

[4]  K. Khunti,et al.  Early Outcomes From the English National Health Service Diabetes Prevention Programme , 2019, Diabetes Care.

[5]  Maria Hagströmer,et al.  Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: systematic review and harmonised meta-analysis , 2019, BMJ.

[6]  K. Khunti,et al.  Impact of Depression and Anxiety on Change to Physical Activity Following a Pragmatic Diabetes Prevention Program Within Primary Care: Pooled Analysis From Two Randomized Controlled Trials , 2019, Diabetes Care.

[7]  R. Stewart,et al.  Intensity and duration of lifestyle interventions for long-term weight loss and association with mortality: a meta-analysis of randomised trials , 2019, BMJ Open.

[8]  Soren Brage,et al.  Physical activity trajectories and mortality: population based cohort study , 2019, BMJ.

[9]  S. Elavsky,et al.  Mobile Health Interventions for Physical Activity, Sedentary Behavior, and Sleep in Adults Aged 50 Years and Older: A Systematic Literature Review. , 2019, Journal of aging and physical activity.

[10]  A. Nicolucci,et al.  Effect of a Behavioral Intervention Strategy on Sustained Change in Physical Activity and Sedentary Behavior in Patients With Type 2 Diabetes: The IDES_2 Randomized Clinical Trial , 2019, JAMA.

[11]  Cindy M. Gray,et al.  The effect of a programme to improve men’s sedentary time and physical activity: The European Fans in Training (EuroFIT) randomised controlled trial , 2019, PLoS medicine.

[12]  Mohammed K. Ali,et al.  Global Diabetes Prevention Interventions: A Systematic Review and Network Meta-analysis of the Real-World Impact on Incidence, Weight, and Glucose , 2018, Diabetes Care.

[13]  M. Bachmann,et al.  Discordance in glycemic categories and regression to normality at baseline in 10,000 people in a Type 2 diabetes prevention trial , 2018, Scientific Reports.

[14]  U. Ekelund,et al.  Physical activity levels in adults and older adults 3–4 years after pedometer-based walking interventions: Long-term follow-up of participants from two randomised controlled trials in UK primary care , 2018, PLoS medicine.

[15]  M. Dörr,et al.  Pitfalls in accelerometer‐based measurement of physical activity: The presence of reactivity in an adult population , 2018, Scandinavian journal of medicine & science in sports.

[16]  A. Brennan,et al.  Assessing the potential return on investment of the proposed UK NHS diabetes prevention programme in different population subgroups: an economic evaluation , 2017, BMJ Open.

[17]  K. Khunti,et al.  Change in Sedentary Time, Physical Activity, Bodyweight, and HbA1c in High-Risk Adults , 2017, Medicine and science in sports and exercise.

[18]  L. Preston,et al.  The impact of Type 2 diabetes prevention programmes based on risk‐identification and lifestyle intervention intensity strategies: a cost‐effectiveness analysis , 2017, Diabetic medicine : a journal of the British Diabetic Association.

[19]  A. Farmer,et al.  Impact of accelerometer and pedometer use on physical activity and glycaemic control in people with Type 2 diabetes: a systematic review and meta‐analysis , 2017, Diabetic medicine : a journal of the British Diabetic Association.

[20]  K. Khunti,et al.  Walking Away from Type 2 diabetes: a cluster randomized controlled trial , 2017, Diabetic medicine : a journal of the British Diabetic Association.

[21]  P. Diggle,et al.  Cost‐effectiveness of population‐based, community, workplace and individual policies for diabetes prevention in the UK , 2017, Diabetic medicine : a journal of the British Diabetic Association.

[22]  K. Khunti,et al.  Cost-effectiveness of a pragmatic structured education intervention for the prevention of type 2 diabetes: economic evaluation of data from the Let's Prevent Diabetes cluster-randomised controlled trial , 2017, BMJ Open.

[23]  R. Wing,et al.  Four-Year Physical Activity Levels among Intervention Participants with Type 2 Diabetes. , 2016, Medicine and science in sports and exercise.

[24]  U. Ekelund,et al.  Short-term and long-term cost-effectiveness of a pedometer-based exercise intervention in primary care: a within-trial analysis and beyond-trial modelling , 2016, BMJ Open.

[25]  J. Usher-Smith,et al.  Cardiovascular risk models for South Asian populations: a systematic review , 2016, International Journal of Public Health.

[26]  F. Sniehotta,et al.  Theoretical explanations for maintenance of behaviour change: a systematic review of behaviour theories , 2016, Health psychology review.

[27]  K. Khunti,et al.  A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let's Prevent Diabetes cluster randomised controlled trial. , 2016, Preventive medicine.

[28]  K. Khunti,et al.  A Text-Messaging and Pedometer Program to Promote Physical Activity in People at High Risk of Type 2 Diabetes: The Development of the PROPELS Follow-On Support Program , 2015, JMIR mHealth and uHealth.

[29]  P. Diggle,et al.  A statistical model to describe longitudinal and correlated metabolic risk factors: the Whitehall II prospective study , 2015, Journal of public health.

[30]  K. Khunti,et al.  PRomotion Of Physical activity through structured Education with differing Levels of ongoing Support for people at high risk of type 2 diabetes (PROPELS): study protocol for a randomized controlled trial , 2015, Trials.

[31]  K. Khunti,et al.  The cost-effectiveness of testing strategies for type 2 diabetes: a modelling study. , 2015, Health technology assessment.

[32]  R. Willke,et al.  Cost-effectiveness analysis alongside clinical trials II-An ISPOR Good Research Practices Task Force report. , 2015, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[33]  D. Wald,et al.  Randomised Trial of Text Messaging on Adherence to Cardiovascular Preventive Treatment (INTERACT Trial) , 2014, PloS one.

[34]  W. Hardeman,et al.  Which Behavior Change Techniques are Associated with Changes in Physical Activity, Diet and Body Mass Index in People with Recently Diagnosed Diabetes? , 2014, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[35]  P. Lin,et al.  A text messaging‐assisted randomized lifestyle weight loss clinical trial among overweight adults in Beijing , 2014, Obesity.

[36]  G. Colditz,et al.  Life years lost and lifetime health care expenditures associated with diabetes in the United States , 2014 .

[37]  F. Naughton,et al.  Randomized controlled trial to assess the short-term effectiveness of tailored web- and text-based facilitation of smoking cessation in primary care (iQuit in Practice) , 2014, Addiction.

[38]  W. Kraus,et al.  Association between change in daily ambulatory activity and cardiovascular events in people with impaired glucose tolerance (NAVIGATOR trial): a cohort analysis , 2014, The Lancet.

[39]  K. Khunti,et al.  Diabetes Prevention in the Real World: Effectiveness of Pragmatic Lifestyle Interventions for the Prevention of Type 2 Diabetes and of the Impact of Adherence to Guideline Recommendations , 2014, Diabetes Care.

[40]  Anne Douglas,et al.  Effect of a lifestyle intervention on weight change in south Asian individuals in the UK at high risk of type 2 diabetes: a family-cluster randomised controlled trial. , 2014, The lancet. Diabetes & endocrinology.

[41]  Seth M Noar,et al.  Efficacy of text messaging-based interventions for health promotion: a meta-analysis. , 2013, Social science & medicine.

[42]  C. Toumazou,et al.  Effectiveness of mobile phone messaging in prevention of type 2 diabetes by lifestyle modification in men in India: a prospective, parallel-group, randomised controlled trial. , 2013, The lancet. Diabetes & endocrinology.

[43]  Yu-ming Chen,et al.  Effects of blood triglycerides on cardiovascular and all-cause mortality: a systematic review and meta-analysis of 61 prospective studies , 2013, Lipids in Health and Disease.

[44]  N. Sattar,et al.  Lower cardiorespiratory fitness contributes to increased insulin resistance and fasting glycaemia in middle-aged South Asian compared with European men living in the UK , 2013, Diabetologia.

[45]  C. Abraham,et al.  The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change Interventions , 2013, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[46]  Alison L Marshall,et al.  Iterative development of MobileMums: a physical activity intervention for women with young children , 2012, International Journal of Behavioral Nutrition and Physical Activity.

[47]  J. Car,et al.  Mobile phone messaging for preventive health care. , 2012, The Cochrane database of systematic reviews.

[48]  Sean P Mullen,et al.  Increasing Physical Activity With Mobile Devices: A Meta-Analysis , 2012, Journal of medical Internet research.

[49]  Darren Flynn,et al.  Changing Physical Activity Behavior in Type 2 Diabetes , 2012, Diabetes Care.

[50]  I. White,et al.  Including all individuals is not enough: Lessons for intention-to-treat analysis , 2012, Clinical trials.

[51]  T. Kohlmann,et al.  Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. , 2012, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[52]  C. Bartlett,et al.  Estimating the current and future costs of Type 1 and Type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs , 2012, Diabetic medicine : a journal of the British Diabetic Association.

[53]  Wolfgang Rathmann,et al.  Prediabetes: a high-risk state for diabetes development , 2012, The Lancet.

[54]  K. Khunti,et al.  Walking away from type 2 diabetes: trial protocol of a cluster randomised controlled trial evaluating a structured education programme in those at high risk of developing type 2 diabetes , 2012, BMC Family Practice.

[55]  K. Khunti,et al.  Let’s prevent diabetes: study protocol for a cluster randomised controlled trial of an educational intervention in a multi-ethnic UK population with screen detected impaired glucose regulation , 2012, Cardiovascular Diabetology.

[56]  Ralph Maddison,et al.  A Development and Evaluation Process for mHealth Interventions: Examples From New Zealand , 2012, Journal of health communication.

[57]  K. Khunti,et al.  Detection of impaired glucose regulation and/or type 2 diabetes mellitus, using primary care electronic data, in a multiethnic UK community setting , 2012, Diabetologia.

[58]  C. Power,et al.  Physical (in)activity over 20 y in adulthood: associations with adult lipid levels in the 1958 British birth cohort. , 2011, Atherosclerosis.

[59]  David R Bassett,et al.  2011 Compendium of Physical Activities: a second update of codes and MET values. , 2011, Medicine and science in sports and exercise.

[60]  A. Montgomery,et al.  Diet or diet plus physical activity versus usual care in patients with newly diagnosed type 2 diabetes: the Early ACTID randomised controlled trial , 2011, The Lancet.

[61]  N. Wareham,et al.  Environmental and psychological correlates of older adult's active commuting. , 2011, Medicine and science in sports and exercise.

[62]  S. Michie,et al.  A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: The CALO-RE taxonomy , 2011, Psychology & health.

[63]  T. Chandola,et al.  Physical activity behaviour and coronary heart disease mortality among South Asian people in the UK: an observational longitudinal study , 2010, Heart.

[64]  K. Khunti,et al.  The potential impact and optimal cut-points of using glycated haemoglobin, HbA1c, to detect people with impaired glucose regulation in a UK multi-ethnic cohort. , 2010, Diabetes research and clinical practice.

[65]  K. Khunti,et al.  Levels of physical activity and relationship with markers of diabetes and cardiovascular disease risk in 5474 white European and South Asian adults screened for type 2 diabetes. , 2010, Preventive medicine.

[66]  K Khunti,et al.  Delivering the diabetes education and self management for ongoing and newly diagnosed (DESMOND) programme for people with newly diagnosed type 2 diabetes: cost effectiveness analysis , 2010, BMJ : British Medical Journal.

[67]  M. Laakso,et al.  Effect of valsartan on the incidence of diabetes and cardiovascular events. , 2010, The New England journal of medicine.

[68]  Diabetes Prevention Program Research Group 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study , 2009, The Lancet.

[69]  C. Abraham,et al.  Effective techniques in healthy eating and physical activity interventions: a meta-regression. , 2009, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[70]  Seth Wolpin,et al.  Pilot study of a cell phone-based exercise persistence intervention post-rehabilitation for COPD , 2009, International journal of chronic obstructive pulmonary disease.

[71]  K. Khunti,et al.  Effectiveness of a Pragmatic Education Program Designed to Promote Walking Activity in Individuals With Impaired Glucose Tolerance , 2009, Diabetes Care.

[72]  J. Shaw,et al.  International Expert Committee Report on the Role of the A1C Assay in the Diagnosis of Diabetes , 2009, Diabetes Care.

[73]  Catrine Tudor-Locke,et al.  Accelerometer-determined steps per day in US adults. , 2009, Medicine and science in sports and exercise.

[74]  K. Newton,et al.  Pedometers and Text Messaging to Increase Physical Activity , 2009, Diabetes Care.

[75]  D. Marrero,et al.  Translating the Diabetes Prevention Program into the community. The DEPLOY Pilot Study. , 2008, American journal of preventive medicine.

[76]  K. Khunti,et al.  ‘Educator talk’ and patient change: some insights from the DESMOND (Diabetes Education and Self Management for Ongoing and Newly Diagnosed) randomized controlled trial , 2008, Diabetic medicine : a journal of the British Diabetic Association.

[77]  A. Sheikh,et al.  Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2 , 2008, BMJ : British Medical Journal.

[78]  Bo Zhang,et al.  The long-term effect of lifestyle interventions to prevent diabetes in the China Da Qing Diabetes Prevention Study: a 20-year follow-up study , 2008, The Lancet.

[79]  Nicola J Cooper,et al.  Different strategies for screening and prevention of type 2 diabetes in adults: cost effectiveness analysis , 2008, BMJ : British Medical Journal.

[80]  K. Khunti,et al.  Effectiveness of the diabetes education and self management for ongoing and newly diagnosed (DESMOND) programme for people with newly diagnosed type 2 diabetes: cluster randomised controlled trial , 2008, BMJ : British Medical Journal.

[81]  M. Pencina,et al.  General Cardiovascular Risk Profile for Use in Primary Care: The Framingham Heart Study , 2008, Circulation.

[82]  Stephen Sutton,et al.  Efficacy of a theory-based behavioural intervention to increase physical activity in an at-risk group in primary care (ProActive UK): a randomised trial , 2008, The Lancet.

[83]  A. Henningsen,et al.  systemfit: A Package for Estimating Systems of Simultaneous Equations in R , 2007 .

[84]  I. Olkin,et al.  Using pedometers to increase physical activity and improve health: a systematic review. , 2007, JAMA.

[85]  R. Albayrak,et al.  The Effects of Weight Loss on Normal Transaminase Levels in Obese Patients , 2007, The American journal of the medical sciences.

[86]  A. Nissinen,et al.  Type 2 Diabetes Prevention in the “Real World” , 2007, Diabetes Care.

[87]  J. S. Sodhi,et al.  Using Internet and Mobile Phone Technology to Deliver an Automated Physical Activity Program: Randomized Controlled Trial , 2007, Journal of medical Internet research.

[88]  K. Khunti,et al.  The role of physical activity in the management of impaired glucose tolerance: a systematic review , 2007, Diabetologia.

[89]  Chris Rissel,et al.  Promoting walking with pedometers in the community: the step-by-step trial. , 2007, American journal of preventive medicine.

[90]  F. Hu,et al.  Physical Activity of Moderate Intensity and Risk of Type 2 Diabetes , 2007, Diabetes Care.

[91]  Nicola J Cooper,et al.  Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis , 2007, BMJ : British Medical Journal.

[92]  J. Lindström,et al.  Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study , 2006, The Lancet.

[93]  S Kumar,et al.  Type 2 diabetes and cardiovascular risk in the UK south Asian community , 2006, Diabetologia.

[94]  David M Williams,et al.  Social-cognitive determinants of physical activity: the influence of social support, self-efficacy, outcome expectations, and self-regulation among participants in a church-based health promotion study. , 2006, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[95]  Elizabeth Broadbent,et al.  The brief illness perception questionnaire. , 2006, Journal of psychosomatic research.

[96]  Urte Scholz,et al.  The role of action control in implementing intentions during the first weeks of behaviour change. , 2006, The British journal of social psychology.

[97]  JoAnn E Manson,et al.  Epidemiological evidence for the role of physical activity in reducing risk of type 2 diabetes and cardiovascular disease. , 2005, Journal of applied physiology.

[98]  P. Raina,et al.  Diagnosis, prognosis, and treatment of impaired glucose tolerance and impaired fasting glucose. , 2005, Evidence report/technology assessment.

[99]  Michael Marmot,et al.  Cohort Profile: the Whitehall II study. , 2005, International journal of epidemiology.

[100]  Catrine Tudor-Locke,et al.  Health benefits of a pedometer-based physical activity intervention in sedentary workers. , 2004, Preventive medicine.

[101]  C. Fischbacher,et al.  How physically active are South Asians in the United Kingdom? A literature review. , 2004, Journal of public health.

[102]  Nicholas H. Wolfinger On writing fieldnotes: collection strategies and background expectancies , 2002 .

[103]  S. Biddle,et al.  A Meta-Analytic Review of the Theories of Reasoned Action and Planned Behavior in Physical Activity: Predictive Validity and the Contribution of Additional Variables , 2002 .

[104]  P. Gollwitzer Implementation intentions: Strong effects of simple plans. , 1999 .

[105]  A Dijkstra,et al.  The development of computer-generated tailored interventions. , 1999, Patient education and counseling.

[106]  P S Freedson,et al.  Calibration of the Computer Science and Applications, Inc. accelerometer. , 1998, Medicine and science in sports and exercise.

[107]  Paul Kind,et al.  Variations in population health status: results from a United Kingdom national questionnaire survey , 1998, BMJ.

[108]  Benjamin Kuipers,et al.  A Description of Think Aloud Method and Protocol Analysis , 1993 .

[109]  R. Snaith,et al.  The Hospital Anxiety And Depression Scale , 2003, Health and quality of life outcomes.

[110]  A. Bandura Self-efficacy: toward a unifying theory of behavioral change. , 1977, Psychological review.

[111]  A. Brennan,et al.  Systematic Review and Meta-Analysis of Randomised Controlled Trials of Psychological Interventions to Improve Glycaemic Control in Adults with Type 2 Diabetes , 2019, Social Science Research Network.

[112]  M. Suhrcke,et al.  Cost-Effectiveness and Value of Information Analysis of Brief Interventions to Promote Physical Activity in Primary Care. , 2018, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[113]  Lena Osterhagen,et al.  Multiple Imputation For Nonresponse In Surveys , 2016 .

[114]  Ulf Ekelund,et al.  Estimating physical activity energy expenditure, sedentary time, and physical activity intensity by self-report in adults. , 2010, The American journal of clinical nutrition.

[115]  Robert J. Vallerand,et al.  A hierarchical model of intrinsic and extrinsic motivation for sport and physical activity. , 2007 .

[116]  Zygimantas Cepaitis,et al.  Physical activity in the prevention of type 2 diabetes: the Finnish diabetes prevention study. , 2005, Diabetes.

[117]  C. Tudor-Locke,et al.  How Many Steps/Day Are Enough? , 2004, Sports medicine.