J Obes Metab Syndr 2022; 31(3): 201-207
Published online September 30, 2022 https://doi.org/10.7570/jomes22027
Copyright © Korean Society for the Study of Obesity.
1Department of Family Medicine, College of Medicine, Kyung Hee University, Seoul; 2Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Seoul; 3Department of Endocrinology and Metabolism, College of Medicine, Kyung Hee University, Seoul; 4Department of Computer Science and Engineering, College of Software, Kyung Hee University, Suwon, Korea
Sang Youl Rhee
Department of Endocrinology and Metabolism, College of Medicine, Kyung Hee University, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
The rapid increase in the obese population is a problem indicates the need for measures to prevent and treat obesity. Since the early 2000s, worldwide digital health has focused on obesity management. Information and communication technology (ICT)-based obesity intervention can be an efficient method for treating obesity and metabolic syndrome, has no time limitations, and is an inexpensive and easily accessible treatment modality for both physicians and patients. Previous studies have confirmed the effects of ICT-based interventions for obesity and metabolic syndrome management for behavioral improvement in lifestyle modification. In addition, ICT-based interventions in obese and metabolic syndrome patients are recommended as part of a comprehensive strategy for weight loss and maintenance. The Committee of IT-convergence Treatment of Metabolic Syndrome was established by the Korean Society for the Study of Obesity in 2021, and had been gathering theoretical and clinical evidence in digital therapeutics fields and developing new methods for managing obesity and metabolic syndrome. As part of this effort, if the “obesity management prototype” is commercialized, it will be available for convenient treatment of individuals with obesity and metabolic syndrome.
Keywords: Cognitive behavioral therapy, Digital technology, Obesity, Telecommunication, Weight loss
Obesity is a significant health problem that is associated with numerous health issues, including cardiovascular disease (heart disease, stroke), type 2 diabetes, musculoskeletal problems, psychosocial disorders, and cancer.1 In 2016, the World Health Organization estimated that more than 650 million adults were obese, which is 13% of the population.2 According to the 2020 Obesity Fact Sheet created by the Korean Society for the Study of Obesity (KSSO), the prevalence of obesity in Korea continuously increased between 2009 (32.6%) and 2018 (38.5%) among the overall population and in both sexes.3 Such a rapid increase in the obese population is a social burden, so measures to prevent and treat obesity are essential.
To prevent obesity from overwhelming clinical practice, patients with obesity should be included in multidisciplinary programs with combined treatment options (diet, physical activity, cognitive-behavioral, pharmacological, and surgical).4,5 However, combined treatment options have often led to suboptimal outcomes due to difficulties in access, cost, lack of personnel and resources, patient treatment adherence, and long-term efficacy of these options. Moreover, about one-third of patients regain the lost weight after the first year of starting these lifestyle interventions.6 Therefore, the challenge of treating obesity is not only to achieve weight loss, but also to maintain it.7
Recently, there has been commitment to developing and implementing digital health technologies for assessment, prevention, and treatment of disease and to promote health and well-being worldwide.8 Digital health is defined broadly as a form in which the use of information and communication technology (ICT) is combined with improving or enabling health and healthcare.9 Since 2020 during the global coronavirus disease 2019 (COVID-19) pandemic, ICT-based interventions have experienced growth in many countries, such as the United States, Europe, China, and Japan. In line with this, ICT-based interventions for obesity have been suggested to be more suitable treatment options.10 The Committee of IT-convergence Treatment of Obesity and Metabolic Syndrome in KSSO (Director Sang Youl Rhee) was established in February 2021. The goals of this committee are as follows: (1) presenting academic rationale for IT-convergence technology for effective treatment of obesity and metabolic syndrome, (2) standardization of digital treatment (DTx) and presenting a general-purpose DTx algorithm, (3) proposal of policy direction for digital dissemination, and (4) establishing a multi-institutional/-disciplinary industry-academic collaboration network for dissemination and supply of treatment techniques for IT-convergence obesity and metabolic syndrome.
ICT-based interventions include web-based platforms (e.g., websites), mobile devices (e.g., cell phones), or wearable devices (e.g., pedometers, accelerometers, Fitbits, and Apple/Galaxy watches).11 Web-based platforms provide education on nutrition and physical activity, self-monitoring of targeted behaviors, goal setting, and more. Mobile devices allow people to use text messages and smartphone applications to monitor their food intake and weight. In the past, wearable technology has been used to set and evaluate the target amount of physical activity as measured by tools such as a pedometer or accelerometer; recently, wearables (e.g., Fitbit, Apple Watch, and Galaxy Watch) have also been used to monitor sleep patterns and other health-related activities.12
The most significant advantages of ICT-based interventions are that they can effectively provide feedback via direct communication and build alliances13 while improving patient convenience and reducing cost and time input.14,15 ICT-based interventions can be used at any time of day to help communicate with healthcare experts to support effective and efficient interventions. Web-based or smartphone application-based management of obesity can improve compliance with interventions. In addition, it can provide opportunities for solving problems related to weight loss and maintenance, including long-term efficacy.16 In particular, ICT-based interventions can compensate for the lack of psychological and behavioral counseling provided by healthcare experts, which can help to achieve and maintain the goal of lifestyle modification for overweight and obesity treatment.17,18 ICT-based interventions that use these advantages effectively enable weight loss and maintenance, and previous studies have shown the benefits of ICT-based interventions.14,19,20 Such effects have been confirmed through studies conducted in Korea.21,22
In the past, ICT-based interventions for obesity treatment have been considered a supplementary means of obesity management through lifestyle modification. Recently, ICT-based obesity treatment has emerged as a parallel or central means of obesity intervention as a part of DTx. Further, randomized controlled clinical trials (RCTs), long-term observational studies, and cost-effectiveness studies to ensure sufficient evidence are warranted.
ICT-based interventions using telephone, internet, smartphone applications, and wearable devices for obesity management effectively support weight loss and weight loss maintenance.23 In a meta-analysis from 2019, the weight loss was significantly higher when a web-based intervention was implemented than when not used (–2.14 kg; 95% confidence interval [CI], –2.65 to –1.64).24 However, this result does not provide conclusive evidence that an ICT-based intervention can be used as an alternative to existing face-to-face programs. Few studies have compared the effects of weight loss and weight maintenance using therapy based on ICT through phones, the internet, and smartphone apps versus conventional behavioral therapy through face-to-face methods.11,20
As a result of a meta-analysis of 23 RCTs that compared the effects of ICT-based interventions and existing management on weight loss, a significant effect (–0.68 kg,
Table 1 summarizes the results of existing studies comparing the effects of obesity treatment on information and communication-based interventions with those of face-to-face treatment.26 To confirm the effect size, comparative advantage, and other factors related to ICT-based interventions compared to conventional (face-to-face) behavioral therapy for weight loss and maintenance, additional studies are needed.
In Korea, when patients were treated for obesity using a mobile app, the average weight loss was –2.73 kg,27 and a combined approach using both an ICT-based intervention and conventional cognitive behavioral therapy showed a more effective weight loss effect than the existing face-to-face treatment (–3.4% vs. –0.7%).28 Overseas, an intensive contact web-based program showed a remarkable effect on weight loss (mean, –4.31 kg; 95% CI, –5.22 to –3.41).29 These results suggest that ICT-based interventions can be most effective when provided multi-dimensionally and accompanied by therapist feedback and support.
The KSSO established the Committee of IT-convergence Treatment of Metabolic Syndrome in 2021, and is working to secure theoretical and academic evidence in related fields by developing new obesity and metabolic syndrome management methods. In particular, the committee is making efforts to improve the completeness of digital health solutions for obesity and metabolic syndrome management, including detailed individual weight goals, individualized interventions, continuous motivation, and maximized possibility of weight loss. The committee has developed a patent-pending prototype that collects and analyzes information for each algorithm and provides appropriate intervention information or methods customized by subject (Fig. 1).
In the future, the KSSO aims to identify and improve additional problems through peer evaluation in conjunction with various expert groups and distribute the findings through an easily accessed open platform (Fig. 2). Furthermore, the committee plans to link this health promotion program to an institutional medical system through multicenter RCTs and real-world studies.
ICT-based interventions have several advantages in weight loss and maintenance in obese/metabolic syndrome patients and can be recommended as part of a comprehensive strategy. The obesity prototype is an ICT-based intervention for obesity and metabolic syndromes that is being developed and supplemented by the Committee of IT-convergence Treatment of Metabolic Syndrome for easy and convenient use in obesity and metabolic syndrome treatment.
The authors declare no conflict of interest.
The authors would like to thank President Ki-jin Kim, Chairman Chang-Beom Lee, and all executives of the Korean Society for the Study of Obesity. In addition, the corresponding author especially thanks Professor Emeriti Young Seol Kim and Young Gil Choi from Kyung Hee University for their exceptional teaching and inspiration.
Study concept and design: SK and SYR; drafting of the manuscript: SK; critical revision of the manuscript: SK, SYR, and Korean Society for the Study of Obesity; administrative, technical, or material support: all authors; and study supervision: RSY.
|Study||Duration (mo)||Intervention||Control||Men||Age (yr)||BMI (kg/m2)||Weight change||Effect|
|Shuger et al.30||9||PA monitoring device||SC||197 (19)||46.8 ± 10.8||33.3 ± 5.2||SWA: –3.55 kg vs. SC: –0.9 kg (no significance)||No difference|
|van Wier et al.31||6||Web-based intervention||Control group||1,386 (67)||43 ± 8.6||29.6 ± 3.5||Internet: –1.9 kg vs. control: –1.0 kg (
|Allen et al.32||6||SP application||IC||68 (22)||44.9 ± 11.1||34.3 ± 3.9||SP: –1.8 ± 3.7 kg vs. IC: –2.5 ± 4.1 kg (
|Steinberg et al.33||6||Smart scale on SP||Text message||91 (25)||44 ± 11||32.15 ± 3.8||Intervention: –6.55% vs. control: –0.35% (
|Harvey-Berino et al.34||6||Web-based intervention||Teleconsultation||481 (80)||46.6 ± 9.9||35.7 ± 5.6||Internet: –5.5 kg vs. in person: –8.0 kg (
|Sullivan et al.35||3/6||Web-based class (VR)||Face to face||20 (15)||31.1 ± 3.6||32.8 ± 5.1||Weight loss: VR: –7.6 % vs. FTF: –10.8% (
|Blomfield et al.36||6||Website CalorieKing||Program materials||159 (100)||47.5 ± 11.0||32.7 ± 3.5||Online: –5.8 ± 5.3 kg vs. resource: –4.4 ± 4.7 kg (
|O’Brien et al.37||4||Web-based management||Personal feedback||289 (41)||41.6 ± 10.2||32.4 ± 3.6||Control: 0.4 ± 2.4 kg vs. basic: –2.2 ± 3.4 kg (
|Thomas et al.38||12||Web-based intervention||PA monitoring||271 (22.5)||33.9 ± 3.7||33.9 ± 3.7||WWOAL: –1.6 kg vs. control: –1.2 kg (
Values are presented as number (%) or mean± standard deviation.
BMI, body mass index; PA, physical activity; SC, standard care; SWA, SenseWear Armband; SP, smartphone; IC, intensive counseling; VR, clinical delivered via virtual reality; FTF, face to face weight management clinic; WWOAL,
Weight Watchers Online plus ActiveLink.