Importance of Active Participation in Obesity Management Through Mobile Health Care Programs: Substudy of a Randomized Controlled Trial

Bumjo Oh, Ga-Hye Yi, Min Kyu Han, Jong Seung Kim, Chang Hee Lee, Belong Cho, Hee Cheol Kang, Bumjo Oh, Ga-Hye Yi, Min Kyu Han, Jong Seung Kim, Chang Hee Lee, Belong Cho, Hee Cheol Kang

Abstract

Background: Due to the prevalence of the westernized dietary pattern and lack of physical activity, the numbers of overweight or obese individuals are increasing, resulting in a growing health burden because of various related diseases. A lifestyle modification approach has additional advantages compared with pharmacological therapies or bariatric surgery. In our randomized controlled trial conducted in 2015, we successfully used a ubiquitous health care (SmartCare) service for patients with metabolic syndrome to achieve a significant weight loss effect. Various useful apps have been developed for the SmartCare Service, which involves using a mobile phone to manage chronic diseases, minimizing time and space restrictions. Many studies have demonstrated weight loss effects using a SmartCare service, but limited data are available regarding the effect of active participation in relation to weight loss.

Objective: We aimed to assess the weight loss effect achieved after using the SmartCare service in terms of adherence and participation. We divided the intervention group of the previous study according to participation level, and analyzed whether there was a significant difference in the outcome.

Methods: We classified participants into 3 groups according to their adherence. Within the intervention group using the SmartCare service, the active group comprised those transmitting anthropometric measurement data using a mobile phone 3 or more times per week or who had a health consultation 5 or more times during a 24-week period. The passive group comprised those who did not adhere to these levels of engagement. The control group comprised those who did not use the SmartCare service. We compared changes in body weight, body mass index (BMI), body fat percentage, waist circumference, and lipid profile among the 3 groups.

Results: We identified 422 participants and analyzed 405, excluding 17 who were missing necessary data for analysis. The active group consisted of 116 participants, compared with 80 in the passive group and 209 in the control group (without SmartCare service). There was a statistically significant difference in improvements to body weight, BMI, body fat percentage, and waist circumference among active participants compared with less active participants and the control group (P<.05). However, the lipid profile changes did not differ significantly between groups.

Conclusions: The level of participation may be related to improved weight-related outcomes, which may improve health outcomes. To maximize the effectiveness of the SmartCare service, encouraging active participation is important.

Trial registration: Clinicaltrials.gov NCT01344811; https://ichgcp.net/clinical-trials-registry/NCT01344811 (Archived by WebCite at http://www.webcitation.org/6alT2MmIB).

Keywords: adherence; concordance; metabolic syndrome; mobile health; physical activity; self-report.

Conflict of interest statement

Conflicts of Interest: None declared.

©Bumjo Oh, Ga-Hye Yi, Min Kyu Han, Jong Seung Kim, Chang Hee Lee, Belong Cho, Hee Cheol Kang. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 03.01.2018.

Figures

Figure 1
Figure 1
Model of SmartCare service.
Figure 2
Figure 2
Flowchart of the intervention.
Figure 3
Figure 3
Selection of the study participants. ITT: intention-to-treat; PP: per protocol.
Figure 4
Figure 4
Changes in anthropometric data during the 24-week period analyzed according to weekly mean number of anthropometric measurements. Error bars indicate standard deviation. BMI: body mass index.
Figure 5
Figure 5
Changes in anthropometric data during the 24-week period analyzed according to total number of health consultations. Error bars indicate standard deviation. BMI: body mass index.

References

    1. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, Singh GM, Gutierrez HR, Lu Y, Bahalim AN, Farzadfar F, Riley LM, Ezzati M, Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group (Body Mass Index) National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants. Lancet. 2011 Feb 12;377(9765):557–67. doi: 10.1016/S0140-6736(10)62037-5.
    1. Kim CS, Ko S, Kwon H, Kim NH, Kim JH, Lim S, Choi SH, Song K, Won JC, Kim DJ, Cha B, Taskforce Team of Diabetes Fact Sheet of the Korean Diabetes Association Prevalence, awareness, and management of obesity in Korea: data from the Korea national health and nutrition examination survey (1998-2011) Diabetes Metab J. 2014 Feb;38(1):35–43. doi: 10.4093/dmj.2014.38.1.35.
    1. Lang A, Froelicher ES. Management of overweight and obesity in adults: behavioral intervention for long-term weight loss and maintenance. Eur J Cardiovasc Nurs. 2006 Jun;5(2):102–14. doi: 10.1016/j.ejcnurse.2005.11.002.
    1. Klein S, Sheard NF, Pi-Sunyer X, Daly A, Wylie-Rosett J, Kulkarni K, Clark NG, American Diabetes Association. North American Association for the Study of Obesity. American Society for Clinical Nutrition Weight management through lifestyle modification for the prevention and management of type 2 diabetes: rationale and strategies: a statement of the American Diabetes Association, the North American Association for the Study of Obesity, and the American Society for Clinical Nutrition. Diabetes Care. 2004 Aug;27(8):2067–73.
    1. Yonhap News . S. Korea tops smartphone penetration rate in 2012 Internet. Seoul, South Korea: The Korea Herald; 2013. [2017-12-20]. .
    1. Kratzke C, Cox C. Smartphone technology and apps: rapidly changing health promotion. Glob J Health Educ Promot. 2012;15(1):72.
    1. Stephens J, Allen J. Mobile phone interventions to increase physical activity and reduce weight: a systematic review. J Cardiovasc Nurs. 2013;28(4):320–9. doi: 10.1097/JCN.0b013e318250a3e7.
    1. Free C, Phillips G, Galli L, Watson L, Felix L, Edwards P, Patel V, Haines A. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Med. 2013;10(1):e1001362. doi: 10.1371/journal.pmed.1001362.
    1. Aguilar-Martínez A, Solé-Sedeño JM, Mancebo-Moreno G, Medina FX, Carreras-Collado R, Saigí-Rubió F. Use of mobile phones as a tool for weight loss: a systematic review. J Telemed Telecare. 2014 Sep;20(6):339–49. doi: 10.1177/1357633X14537777.
    1. Oh B, Cho B, Han MK, Choi H, Lee MN, Kang H, Lee CH, Yun H, Kim Y. The effectiveness of mobile phone-based care for weight control in metabolic syndrome patients: randomized controlled trial. JMIR Mhealth Uhealth. 2015;3(3):e83. doi: 10.2196/mhealth.4222.
    1. Isomaa B, Almgren P, Tuomi T, Forsén B, Lahti K, Nissén M, Taskinen MR, Groop L. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care. 2001 Apr;24(4):683–9.
    1. Haffner SM, Valdez RA, Hazuda HP, Mitchell BD, Morales PA, Stern MP. Prospective analysis of the insulin-resistance syndrome (syndrome X) Diabetes. 1992 Jun;41(6):715–22.
    1. Lim S, Shin H, Song JH, Kwak SH, Kang SM, Won YJ, Choi SH, Cho SI, Park KS, Lee HK, Jang HC, Koh KK. Increasing prevalence of metabolic syndrome in Korea: the Korean National Health and Nutrition Examination Survey for 1998-2007. Diabetes Care. 2011 Jun;34(6):1323–8. doi: 10.2337/dc10-2109.
    1. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults Executive summary of the 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) JAMA. 2001 May 16;285(19):2486–97.
    1. World Health Organization, Regional Office for the Western Pacific . The Asia-Pacific Perspective: Redefining Obesity and its Treatment. Sydney, Australia: Health Communications Australia; 2000. .
    1. Oh SW, Shin S, Yun YH, Yoo T, Huh B. Cut-off point of BMI and obesity-related comorbidities and mortality in middle-aged Koreans. Obes Res. 2004 Dec;12(12):2031–40. doi: 10.1038/oby.2004.254.
    1. Chun MY. Validity and reliability of Korean version of International Physical Activity Questionnaire short form in the elderly. Korean J Fam Med. 2012 May;33(3):144–51. doi: 10.4082/kjfm.2012.33.3.144.
    1. Shim Y, Paik H. Reanalysis of 2007 Korean National Health and Nutrition Examination Survey (2007 KNHANES) results by CAN-Pro 3 Nutrient Database. Korean J Nutr. 2009;42(6):577–95. doi: 10.4163/kjn.2009.42.6.577. doi: 10.4163/kjn.2009.42.6.577.
    1. VanWormer JJ, Linde JA, Harnack LJ, Stovitz SD, Jeffery RW. Self-weighing frequency is associated with weight gain prevention over 2 years among working adults. Int J Behav Med. 2012 Sep;19(3):351–8. doi: 10.1007/s12529-011-9178-1.
    1. Killikelly C, He Z, Reeder C, Wykes T. Improving adherence to web-based and mobile technologies for people with psychosis: systematic review of new potential predictors of adherence. JMIR Mhealth Uhealth. 2017 Jul 20;5(7):e94. doi: 10.2196/mhealth.7088.
    1. Beratarrechea A, Lee AG, Willner JM, Jahangir E, Ciapponi A, Rubinstein A. The impact of mobile health interventions on chronic disease outcomes in developing countries: a systematic review. Telemed J E Health. 2014 Jan;20(1):75–82. doi: 10.1089/tmj.2012.0328.
    1. Choi E, Jeong Y. U-health for management of chronic diseases-physical activity and therapeutic exercise. J Korean Med Assoc. 2009;52(12):1154–1163. doi: 10.5124/jkma.2009.52.12.1154. doi: 10.5124/jkma.2009.52.12.1154.
    1. Song T, Ryu S, Lee SH. U-health service for managing chronic disease: a case study on managing metabolic syndrome in a health center in South Korea. Healthc Inform Res. 2011 Dec;17(4):260–6. doi: 10.4258/hir.2011.17.4.260.
    1. van der Weegen S, Verwey R, Spreeuwenberg M, Tange H, van der Weijden T, de Witte L. The development of a mobile monitoring and feedback tool to stimulate physical activity of people with a chronic disease in primary care: a user-centered design. JMIR Mhealth Uhealth. 2013;1(2):e8. doi: 10.2196/mhealth.2526.
    1. Park DK, Kim JH, Kim JK, Jung EY, Lee YH. U-health service model for managing health of chronic patients in multi-platform environment. J Korea Contents Assoc. 2011;11(8):23–32.
    1. Wang J, Wang Y, Wei C, Yao NA, Yuan A, Shan Y, Yuan C. Smartphone interventions for long-term health management of chronic diseases: an integrative review. Telemed J E Health. 2014 Jun;20(6):570–83. doi: 10.1089/tmj.2013.0243.
    1. Jones RCM, Hyland ME, Hanney K, Erwin J. A qualitative study of compliance with medication and lifestyle modification in chronic obstructive pulmonary disease (COPD) Prim Care Respir J. 2004 Sep;13(3):149–54. doi: 10.1016/j.pcrj.2004.05.006. doi: 10.1016/j.pcrj.2004.05.006.
    1. Alm-Roijer C, Stagmo M, Udén G, Erhardt L. Better knowledge improves adherence to lifestyle changes and medication in patients with coronary heart disease. Eur J Cardiovasc Nurs. 2004 Dec;3(4):321–30. doi: 10.1016/j.ejcnurse.2004.05.002.
    1. Sokol MC, McGuigan KA, Verbrugge RR, Epstein RS. Impact of medication adherence on hospitalization risk and healthcare cost. Med Care. 2005 Jun;43(6):521–30.
    1. DiMatteo MR, Giordani PJ, Lepper HS, Croghan TW. Patient adherence and medical treatment outcomes: a meta-analysis. Med Care. 2002 Sep;40(9):794–811. doi: 10.1097/01.MLR.0000024612.61915.2D.
    1. Loh A, Leonhart R, Wills CE, Simon D, Härter M. The impact of patient participation on adherence and clinical outcome in primary care of depression. Patient Educ Couns. 2007 Jan;65(1):69–78. doi: 10.1016/j.pec.2006.05.007.
    1. Rasmussen JN, Chong A, Alter DA. Relationship between adherence to evidence-based pharmacotherapy and long-term mortality after acute myocardial infarction. JAMA. 2007 Jan 10;297(2):177–86. doi: 10.1001/jama.297.2.177.
    1. Yamaoka K, Tango T. Effects of lifestyle modification on metabolic syndrome: a systematic review and meta-analysis. BMC Med. 2012 Nov 14;10:138. doi: 10.1186/1741-7015-10-138.
    1. Thoma C, Day CP, Trenell MI. Lifestyle interventions for the treatment of non-alcoholic fatty liver disease in adults: a systematic review. J Hepatol. 2012 Jan;56(1):255–66. doi: 10.1016/j.jhep.2011.06.010.

Source: PubMed

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