Acknowledgement
We would like to thank all participants. We also thank the Noom Coach, Inc. (Seoul, South Korea) for technological assistance.
References
- World Health Organization. Obesity and overweight [Internet]. Geneva: World Health Organization; 2021 [cited 2016 April 24]. Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.
- Korea Centers for Disease Control and Prevention. Korea Health Statistics 1998: Korea National Health and Nutrition Examination Survey (KNHANES I). Cheongju: Korea Centers for Disease Control and Prevention; 2012.
- Korea Centers for Disease Control and Prevention, Korea Health Statistics 2021: Korea National Health and Nutrition Examination Survey (KNHANES VIII-3). Cheongju: Korea Centers for Disease Control and Prevention; 2022.
- World Health Organization. Atlas of eHealth country profiles 2015: the use of eHealth in support of universal health coverage based on the findings of the 2015 global survey on eHealth [Internet]. Geneva: World Health Organization; 2020 [cited 2015 April 23] Available from: https://www.who.int/publications/i/item/9789241565219.
- 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:e1001362.
- Fakih El Khoury C, Karavetian M, Halfens RJ, Crutzen R, Khoja L, Schols JM. The effects of dietary mobile apps on nutritional outcomes in adults with chronic diseases: a systematic review and meta-analysis. J Acad Nutr Diet 2019;119:626-51. https://doi.org/10.1016/j.jand.2018.11.010
- Turner-McGrievy GM, Wilcox S, Boutte A, Hutto BE, Singletary C, Muth ER, Hoover AW. The dietary intervention to enhance tracking with mobile devices (DIET Mobile) study: a 6-month randomized weight loss trial. Obesity (Silver Spring) 2017;25:1336-42. https://doi.org/10.1002/oby.21889
- Stephens JD, Yager AM, Allen J. Smartphone technology and text messaging for weight loss in young adults: a randomized controlled trial. J Cardiovasc Nurs 2017;32:39-46. https://doi.org/10.1097/JCN.0000000000000307
- Ross KM, Wing RR. Impact of newer self-monitoring technology and brief phone-based intervention on weight loss: a randomized pilot study. Obesity (Silver Spring) 2016;24:1653-9. https://doi.org/10.1002/oby.21536
- Thomas JG, Bond DS, Raynor HA, Papandonatos GD, Wing RR. Comparison of smartphone-based behavioral obesity treatment with gold standard group treatment and control: a randomized trial. Obesity (Silver Spring) 2019;27:572-80. https://doi.org/10.1002/oby.22410
- Wang J, Cai C, Padhye N, Orlander P, Zare M. A behavioral lifestyle intervention enhanced with multiple-behavior self-monitoring using mobile and connected tools for underserved individuals with type 2 diabetes and comorbid overweight or obesity: pilot comparative effectiveness trial. JMIR Mhealth Uhealth 2018;6:e92.
- Wharton CM, Johnston CS, Cunningham BK, Sterner D. Dietary self-monitoring, but not dietary quality, improves with use of smartphone app technology in an 8-week weight loss trial. J Nutr Educ Behav 2014;46:440-4. https://doi.org/10.1016/j.jneb.2014.04.291
- Spring B, Pellegrini CA, Pfammatter A, Duncan JM, Pictor A, McFadden HG, Siddique J, Hedeker D. Effects of an abbreviated obesity intervention supported by mobile technology: the ENGAGED randomized clinical trial. Obesity (Silver Spring) 2017;25:1191-8. https://doi.org/10.1002/oby.21842
- Dunn WB, Ellis DI. Metabolomics: current analytical platforms and methodologies. Trends Analyt Chem 2005;24:285-94. https://doi.org/10.1016/j.trac.2004.11.021
- Dunn WB, Erban A, Weber RJ, Creek DJ, Brown M, Breitling R, Hankemeier T, Goodacre R, Neumann S, Kopka J, et al. Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics. Metabolomics 2013;9:44-66. https://doi.org/10.1007/s11306-012-0434-4
- Geidenstam N, Al-Majdoub M, Ekman M, Spegel P, Ridderstrale M. Metabolite profiling of obese individuals before and after a one year weight loss program. Int J Obes 2017;41:1369-78. https://doi.org/10.1038/ijo.2017.124
- Kang M, Yoo HJ, Kim M, Kim M, Lee JH. Metabolomics identifies increases in the acylcarnitine profiles in the plasma of overweight subjects in response to mild weight loss: a randomized, controlled design study. Lipids Health Dis 2018;17:237.
- Institute of Medicine. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington, D.C.: The National Academies Press; 2005.
- American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2014;37 Suppl 1:S81-90. https://doi.org/10.2337/dc14-S081
- National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). 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;106:3143-421. https://doi.org/10.1161/circ.106.25.3143
- Uppal K, Ma C, Go YM, Jones DP, Wren J. xMWAS: a data-driven integration and differential network analysis tool. Bioinformatics 2018;34:701-2. https://doi.org/10.1093/bioinformatics/btx656
- Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, Cheng D, Jewell K, Arndt D, Sawhney S, et al. HMDB: the Human Metabolome Database. Nucleic Acids Res 2007;35:D521-6. https://doi.org/10.1093/nar/gkl923
- Xia J, Psychogios N, Young N, Wishart DS. MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res 2009;37:W652-60. https://doi.org/10.1093/nar/gkp356
- Xia J, Wishart DS. MetPA: a web-based metabolomics tool for pathway analysis and visualization. Bioinformatics 2010;26:2342-4. https://doi.org/10.1093/bioinformatics/btq418
- Ahn JS, Lee H, Kim J, Park H, Kim DW, Lee JE. Use of a smartphone app for weight loss versus a paper-based dietary diary in overweight adults: randomized controlled trial. JMIR Mhealth Uhealth 2020;8:e14013.
- Burke LE, Styn MA, Sereika SM, Conroy MB, Ye L, Glanz K, Sevick MA, Ewing LJ. Using mHealth technology to enhance self-monitoring for weight loss: a randomized trial. Am J Prev Med 2012;43:20-6. https://doi.org/10.1016/j.amepre.2012.03.016
- Laing BY, Mangione CM, Tseng CH, Leng M, Vaisberg E, Mahida M, Bholat M, Glazier E, Morisky DE, Bell DS. Effectiveness of a smartphone application for weight loss compared with usual care in overweight primary care patients: a randomized, controlled trial. Ann Intern Med 2014;161:S5-12. https://doi.org/10.7326/M13-3005
- Wiss DA, Avena N, Rada P. Sugar addiction: from evolution to revolution. Front Psychiatry 2018;9:545.
- Avena NM, Bocarsly ME. Dysregulation of brain reward systems in eating disorders: neurochemical information from animal models of binge eating, bulimia nervosa, and anorexia nervosa. Neuropharmacology 2012;63:87-96. https://doi.org/10.1016/j.neuropharm.2011.11.010
- Pahlavani M, Razafimanjato F, Ramalingam L, Kalupahana NS, Moussa H, Scoggin S, Moustaid-Moussa N. Eicosapentaenoic acid regulates brown adipose tissue metabolism in high-fat-fed mice and in clonal brown adipocytes. J Nutr Biochem 2017;39:101-9. https://doi.org/10.1016/j.jnutbio.2016.08.012
- Serini S, Fasano E, Piccioni E, Cittadini AR, Calviello G. Dietary n-3 polyunsaturated fatty acids and the paradox of their health benefits and potential harmful effects. Chem Res Toxicol 2011;24:2093-105. https://doi.org/10.1021/tx200314p
- Richard JP. Mechanism for the formation of methylglyoxal from triosephosphates. Biochem Soc Trans 1993;21:549-53. https://doi.org/10.1042/bst0210549
- Lu M, Zhou L, Stanley WC, Cabrera ME, Saidel GM, Yu X. Role of the malate-aspartate shuttle on the metabolic response to myocardial ischemia. J Theor Biol 2008;254:466-75. https://doi.org/10.1016/j.jtbi.2008.05.033
- Hirata F, Axelrod J. Phospholipid methylation and biological signal transmission. Science 1980;209:1082-90. https://doi.org/10.1126/science.6157192
- DeLong CJ, Shen YJ, Thomas MJ, Cui Z. Molecular distinction of phosphatidylcholine synthesis between the CDP-choline pathway and phosphatidylethanolamine methylation pathway. J Biol Chem 1999;274:29683-8. https://doi.org/10.1074/jbc.274.42.29683
- Jacobs RL, Zhao Y, Koonen DP, Sletten T, Su B, Lingrell S, Cao G, Peake DA, Kuo MS, Proctor SD, et al. Impaired de novo choline synthesis explains why phosphatidylethanolamine N-methyltransferase-deficient mice are protected from diet-induced obesity. J Biol Chem 2010;285:22403-13. https://doi.org/10.1074/jbc.M110.108514
- Schippers M, Adam PC, Smolenski DJ, Wong HT, de Wit JB. A meta-analysis of overall effects of weight loss interventions delivered via mobile phones and effect size differences according to delivery mode, personal contact, and intervention intensity and duration. Obes Rev 2017;18:450-9. https://doi.org/10.1111/obr.12492
- Allen JK, Stephens J, Dennison Himmelfarb CR, Stewart KJ, Hauck S. Randomized controlled pilot study testing use of smartphone technology for obesity treatment. J Obes 2013;2013:151597.
- Carter MC, Burley VJ, Nykjaer C, Cade JE. Adherence to a smartphone application for weight loss compared to website and paper diary: pilot randomized controlled trial. J Med Internet Res 2013;15:e32.