A lifestyle intervention supported by mobile health technologies to improve the cardiometabolic risk profile of individuals at risk for cardiovascular disease and type 2 diabetes: study rationale and protocol

Melanie I Stuckey, Sheree Shapiro, Dawn P Gill, Robert J Petrella, Melanie I Stuckey, Sheree Shapiro, Dawn P Gill, Robert J Petrella

Abstract

Background: Metabolic syndrome is a cluster of cardiovascular risk factors that greatly increase the risk of developing cardiovascular disease and type 2 diabetes. Regular exercise improves the risk profile, but most people do not successfully change their exercise habits to beneficially reduce risk. Tailored exercise prescribed by a family physician has shown promise as a means to increase fitness and reduce cardiometabolic risk, but optimal implementation practices remain unknown. Mobile health technologies have proved to be a beneficial tool to achieve blood pressure and blood glucose control in patients with diabetes. These technologies may address the limited access to health interventions in rural and remote regions. However, the potential as a tool to support exercise-based prevention activities is not well understood. This study was undertaken to investigate the effects of a tailored exercise prescription alone or supported by mobile health technologies to improve metabolic syndrome and related cardiometabolic risk factors in rural community-dwelling adults at risk for cardiovascular disease and type 2 diabetes.

Methods/design: Adults (n = 149) with at least two metabolic syndrome risk factors were recruited from rural communities and randomized to either: 1) an intervention group receiving an exercise prescription and devices for monitoring of risk factors with a smartphone data portal equipped with a mobile health application; or 2) an active control group receiving only an exercise prescription. All participants reported to the research centre at baseline, and at 12-, 24- and 52-week follow-up visits for measurement of anthropometrics and blood pressure and for a blood draw to test blood-borne markers of cardiometabolic health. Vascular and autonomic function were examined. Fitness was assessed and exercise prescribed according to the Step Test and Exercise Prescription protocol.

Discussion: This study tested the effects of a prescriptive exercise intervention alone, versus one supported by mobile health technology on cardiometabolic risk factors. The intervention was designed to be translated into clinical or community-based programming. Results will contribute to the current literature by investigating the utility of mobile health technology support for exercise prescription interventions to improve cardiometabolic risk status and maintain improvements over time; particularly in rural communities.

Clinical trials registration: NCT01944124.

Figures

Figure 1
Figure 1
Step Test and Exercise Prescription (STEP™) protocol.

References

    1. Mendis S, Puska P, Norrving B. Global atlas on cardiovascular disease prevention and control. Geneva, Switzerland: World Health Organization; 2011.
    1. Centers for Disease Control and Prevention. National diabetes fact sheet: national estimates and general information on diabetes and prediabetes in the United States, 2011. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2011.
    1. Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart J, James WPT, Loria CM, Smith SC. Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity. Circulation. 2009;13(16):1640–1645. doi: 10.1161/CIRCULATIONAHA.109.192644.
    1. Leiter LA, Fitchett DH, Gilbert RE, Gupta M, Mancini GB, McFarlane PA, Ross R, Teoh H, Verma S, Anand S, Camelon K, Chow CM, Cox JL, Despres JP, Genest J, Harris SB, Lau DC, Lewanczuk R, Liu PP, Lonn EM, McPherson R, Poirier P, Qaadri S, Rabasa-Lhoret R, Rabkin SW, Sharma AM, Steele AW, Stone JA, Tardif JC, Tobe S, Ur E. Cardiometabolic Risk Working Group: Executive Committee. Cardiometabolic risk in Canada: a detailed analysis and position paper by the cardiometabolic risk working group. Can J Cardiol. 2011;13(2):e1–e33. doi: 10.1016/j.cjca.2010.12.054.
    1. Katzmarzyk PT, Leon AS, Wilmore JH, Skinner JS, Rao DC, Rankinen T, Bouchard C. Targeting the metabolic syndrome with exercise: evidence from the HERITAGE Family Study. Med Sci Sports Exerc. 2003;13(10):1703–1709. doi: 10.1249/01.MSS.0000089337.73244.9B.
    1. Pattyn N, Cornelissen VA, Eshghi SRT, Vanhees L. The effect of exercise on the cardiovascular risk factors constituting the metabolic syndrome: a meta-analysis of controlled trials. Sports Med. 2013;13(2):121–133. doi: 10.1007/s40279-012-0003-z.
    1. Oh EG, Bang SY, Hyun SS, Kim SH, Chu SH, Jeon JY, Im JA, Lee MK, Lee JE. Effects of a 6-month lifestyle modification intervention on the cardiometabolic risk factors and health-related qualities of life in women with metabolic syndrome. Metabolism. 2010;13(7):1035–1043. doi: 10.1016/j.metabol.2009.10.027.
    1. Tjønna AE, Lee SJ, Rognmo Ø, Stølen TO, Bye A, Haram PM, Loennechen JP, Al-Share QY, Skogvoll E, Slørdahl SA, Kemi OJ, Najjar SM, Wisløff U. Aerobic interval training versus continuous moderate exercise as a treatment for the metabolic syndrome: A pilot study. Circulation. 2008;13(4):346–354. doi: 10.1161/CIRCULATIONAHA.108.772822.
    1. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM. Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;13(6):393–403.
    1. Colley RC, Garriguet D, Janssen I, Craig CL, Clarke J, Tremblay MS. Physical activity of Canadian adults: accelerometer results from the 2007 to 2009 Canadian Health Measures Survey. Health Rep. 2011;13(1):7–14.
    1. Tucker JM, Welk GJ, Beyler NK. Physical activity in U.S. Adults: compliance with the physical activity guidelines for Americans. Am J Prev Med. 2011;13(4):454–461. doi: 10.1016/j.amepre.2010.12.016.
    1. Elley CR, Kerse N, Arroll B, Robinson E. Effectiveness of counselling patients on physical activity in general practice: cluster randomised controlled trial. BMJ. 2003;13(7393):93.
    1. Orrow G, Kinmonth AL, Sanderson S, Sutton S. Effectiveness of physical activity promotion based in primary care: systematic review and meta-analysis of randomised controlled trials. BMJ. 2012;13:e1389. doi: 10.1136/bmj.e1389.
    1. Petrella RJ, Lattanzio CN. Does counseling help patients get active? Systematic review of the literature. Can Fam Phys. 2002;13:72–80.
    1. Liang X, Wang Q, Yang X, Cao J, Chen J, Mo X, Huang J, Wang L, Gu D. Effect of mobile phone intervention for diabetes on glycaemic control: A meta-analysis. Diabetic Med. 2011;13(4):455–463. doi: 10.1111/j.1464-5491.2010.03180.x.
    1. Green BB, Cook AJ, Ralston JD, Fishman PA, Catz SL, Carlson J, Carrell D, Tyll L, Larson EB, Thompson RS. Effectiveness of home blood pressure monitoring, web communication, and pharmacist care on hypertension control: A randomized controlled trial. JAMA. 2008;13(24):2857–2867. doi: 10.1001/jama.299.24.2857.
    1. Logan AG, Jane Irvine M, McIsaac WJ, Tisler A, Rossos PG, Easty A, Feig DS, Cafazzo JA. Effect of home blood pressure telemonitoring with self-care support on uncontrolled systolic hypertension in diabetics. Hypertension. 2012;13(1):51–57. doi: 10.1161/HYPERTENSIONAHA.111.188409.
    1. Park M, Kim H, Kim K. Cellular phone and Internet-based individual intervention on blood pressure and obesity in obese patients with hypertension. Int J Med Inf. 2009;13(10):704–710. doi: 10.1016/j.ijmedinf.2009.06.004.
    1. Jung H, Lee B, Lee J, Kwon Y, Song H. Efficacy of a programme for workers with metabolic syndrome based on an e-health system in the workplace: a pilot study. J Telemed Telecare. 2012;13:339–343. doi: 10.1258/jtt.2012.120318.
    1. Ontario Ministry of Health and Long-Term Care. .
    1. Stuckey M, Fulkerson R, Read E, Russell-Minda E, Munoz C, Kleinstiver P, Petrella R. Remote monitoring technologies for the prevention of metabolic syndrome: the Diabetes and Technology for Increased Activity (DaTA) study. J Diabetes Sci Technol. 2011;13(4):936–944.
    1. Stuckey M, Russell-Minda E, Read E, Munoz C, Shoemaker K, Kleinstiver P, Petrella R. Diabetes and Technology for Increased Activity (DaTA) study: results of a remote monitoring intervention for prevention of metabolic syndrome. J Diabetes Sci Technol. 2011;13(4):928–935.
    1. Stuckey MI, Kiviniemi AM, Petrella RJ. Diabetes and Technology for Increased Activity (DaTA Study): The effects of exercise and technology on heart rate variability and metabolic syndrome risk factors. Front Enocrinol. 2013;13(4):121.
    1. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002;13(25):3143–3421.
    1. Alberti KG, Zimmet P, Shaw J. IDF Epidemiology Task Force Consensus Group. The metabolic syndrome--a new worldwide definition. Lancet. 2005;13(9491):1059–1062. doi: 10.1016/S0140-6736(05)67402-8.
    1. Peretz A, Leotta DF, Sullivan JH, Trenga CA, Sands FN, Aulet MR, Paun M, Gill EA, Kaufman JD. Flow mediated dilation of the brachial artery: an investigation of methods requiring further standardization. BMC Cardiovasc Disord. 2007;13(11) doi:10.1186/1471-2261-7-11.
    1. Petrella RJ, Koval JJ, Cunningham DA, Paterson DH. A self-paced step test to predict aerobic fitness in older adults in the primary care clinic. J Am Geriatr Soc. 2001;13(5):632–638. doi: 10.1046/j.1532-5415.2001.49124.x.
    1. Stuckey MI, Knight E, Petrella RJ. The step test and exercise prescription tool in primary care: a critical review. Crit Rev Phys Rehabil Med. 2012;13(1–2):109–123.
    1. Haskell WL, Lee I, Pate RR, Powell KE, Blair SN, Franklin BA, Macera CA, Heath GW, Thompson PD, Bauman A. Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation. 2007;13(9):1081–1093.
    1. Global recommendations on physical activity for health 2010. Global recommendations on physical activity for health 2010. Geneva, Switzerland: The World Health Organization; 2010.
    1. Tudor-Locke C, Bassett DR. How many steps/Day Are enough? Preliminary pedometer indices for public health. Sports Med. 2004;13(1):1–8. doi: 10.2165/00007256-200434010-00001.
    1. Ware JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36)). I. Conceptual framework and item selection. Med Care. 1992;13(6):473–483. doi: 10.1097/00005650-199206000-00002.
    1. McHorney CA, Ware JE, Raczek AE. The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care. 1993;13(3):247–263. doi: 10.1097/00005650-199303000-00006.
    1. McHorney CA, Ware JE, Lu JF, Sherbourne CD. The MOS 36-item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Med Care. 1994;13(1):40–66. doi: 10.1097/00005650-199401000-00004.
    1. Toobert DJ, Hampson SE, Glasgow RE. The summary of diabetes self-care activities measure: results from 7 studies and a revised scale. Diabetes Care. 2000;13(7):943–950. doi: 10.2337/diacare.23.7.943.
    1. Nigg CR, Riebe D. In: Promoting exercise and behavior change in older adults: interventions with the Transtheoretical Model. Burbank P, Riebe D, editor. New York: Springer Publishing Company; 2002. The Transtheoretical Model: Research review of exercise behavior in older adults; pp. 147–180.
    1. Atkin S, Manley J, Petrella RJ. Development and validation of a stage-matched nutrition lifestyle intervention for primary care physicians. Med Sci Sports Exerc. 2005;13:S368.
    1. Nichols W, O’Rourke M. McDonald’s Blood Flow in Arteries: Theoretical, experimental and clinical principles. London, UK: Hodder Arnold; 2005.
    1. Corretti MC, Anderson TJ, Benjamin EJ, Celermajer D, Charbonneau F, Creager MA, Deanfield J, Drexler H, Gerhard-Herman M, Herrington D, Vallance P, Vita J, Vogel R. International Brachial Artery Reactivity Task Force. Guidelines for the ultrasound assessment of endothelial-dependent flow-mediated vasodilation of the brachial artery: a report of the International Brachial Artery Reactivity Task Force. J Am Coll Cardiol. 2002;13(2):257–265. doi: 10.1016/S0735-1097(01)01746-6.
    1. Schulz KF, Altman DG, Moher D. CONSORT Group. CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. BMC Med. 2010;13:18. doi: 10.1186/1741-7015-8-18.
    1. R Development Core Team. The R Foundation for Statistical Computing. .
    1. Statistics Canada. 2010 health profile. .
    1. Carroll S, Dudfield M. What is the relationship between exercise and metabolic abnormalities? A review of the metabolic syndrome. Sports Med. 2004;13(6):371–418. doi: 10.2165/00007256-200434060-00004.
    1. Lakka TA, Laaksonen DE. Physical activity in prevention and treatment of the metabolic syndrome. Appl Physiol Nutr Metab. 2007;13(1):76–88. doi: 10.1139/h06-113.
    1. Chudyk A, Petrella RJ. Effects of exercise on cardiovascular risk factors in type 2 diabetes: a meta-analysis. Diabetes Care. 2011;13(5):1228–1237. doi: 10.2337/dc10-1881.
    1. Hautala AJ, Mäkikallio TH, Kiviniemi A, Laukkanen RT, Nissilä S, Huikuri HV, Tulppo MP. Heart rate dynamics after controlled training followed by a home-based exercise program. Eur J Appl Physiol. 2004;13(3):289–297.
    1. Pagkalos M, Koutlianos N, Kouidi E, Pagkalos E, Mandroukas K, Deligiannis A. Heart rate variability modifications following exercise training in type 2 diabetic patients with definite cardiac autonomic neuropathy. Br J Sports Med. 2008;13(1):47–54.
    1. Tulppo MP, Hautala AJ, Mäkikallio TH, Laukkanen RT, Nissilä S, Hughson RL, Huikuri HV. Effects of aerobic training on heart rate dynamics in sedentary subjects. J Appl Physiol. 2003;13(1):364–372.
    1. Aizawa K, Shoemaker JK, Overend TJ, Petrella RJ. Effects of lifestyle modification on central artery stiffness in metabolic syndrome subjects with pre-hypertension and/or pre-diabetes. Diabetes Res Clin Pract. 2009;13(2):249–256. doi: 10.1016/j.diabres.2008.11.016.
    1. Aizawa K, Shoemaker JK, Overend TJ, Petrella RJ. Metabolic syndrome, endothelial function and lifestyle modification. Diab Vasc Dis Res. 2009;13(3):181–189. doi: 10.1177/1479164109336375.
    1. Carnethon MR, Prineas RJ, Temprosa M, Zhang ZM, Uwaifo G, Molitch ME. Diabetes Prevention Program Research Group. The association among autonomic nervous system function, incident diabetes, and intervention arm in the Diabetes Prevention Program. Diabetes Care. 2006;13(4):914–919. doi: 10.2337/diacare.29.04.06.dc05-1729.
    1. Katzmarzyk PT, Church TS, Blair SN. Cardiorespiratory fitness attenuates the effects of the metabolic syndrome on all-cause and cardiovascular disease mortality in men. Arch Intern Med. 2004;13(10):1092–1097. doi: 10.1001/archinte.164.10.1092.
    1. Lindstrom J, Ilanne-Parikka P, Peltonen M, Aunola S, Eriksson JG, Hemio K, Hamalainen H, Harkonen P, Keinanen-Kiukaanniemi S, Laakso M, Louheranta A, Mannelin M, Paturi M, Sundvall J, Valle TT, Uusitupa M, Tuomilehto J. Finnish Diabetes Prevention Study Group. Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study. Lancet. 2006;13(9548):1673–1679. doi: 10.1016/S0140-6736(06)69701-8.

Source: PubMed

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