2. Apovian CM. 2016; Obesity: definition, comorbidities, causes, and burden. Am J Manag Care. 22(7 Suppl):s176–s185.
4. Jensen MD, Ryan DH, Apovian CM, et al. 2014; 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. J Am Coll Cardiol. 63(25 Part B):2985–3023. DOI:
10.1161/01.cir.0000437739.71477.ee. PMID:
24222017. PMCID:
PMC5819889.
8. Stelmach-Mardas M, Rodacki T, Dobrowolska-Iwanek J, et al. 2016; Link between food energy density and body weight changes in obese adults. Nutrients. 8:229. DOI:
10.3390/nu8040229. PMID:
27104562. PMCID:
PMC4848697.

10. Wang L, Wang H, Zhang B, Popkin BM, Du S. 2020; Elevated fat intake increases body weight and the risk of overweight and obesity among Chinese adults: 1991-2015 trends. Nutrients. 12:3272. DOI:
10.3390/nu12113272. PMID:
33114561. PMCID:
PMC7694029.

11. Lee SI. 2010; Metabolism & nutritional support in obesity. Surg Metab Nutr. 1:12–16.
12. U.S. Department of Health and Human Services and U.S. Department of Agriculture. 2015-2020 dietary guidelines for Americans, 8th ed. Washington, D.C: U.S. Department of Health and Human Services;2015.
13. Sacks FM, Bray GA, Carey VJ, et al. 2009; Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates. N Engl J Med. 360:859–873. DOI:
10.1056/NEJMoa0804748. PMID:
19246357. PMCID:
PMC2763382.

14. Bray GA, Siri-Tarino PW. 2016; The role of macronutrient content in the diet for weight management. Endocrinol Metab Clin North Am. 45:581–604. DOI:
10.1016/j.ecl.2016.04.009. PMID:
27519132.

15. Lee SH. Metabolism, Obesity, and Nutrition Research Group of The Korean College of Helicobacter and Upper Gastrointestinal Research. 2023. Dietary Management of Obesity. 1st ed. Nutritional management of upper gastrointestinal diseases. Daehanuihak;Seoul: p. 160–170.
16. Howell S, Kones R. 2017; "Calories in, calories out" and macronutrient intake: the hope, hype, and science of calories. Am J Physiol Endocrinol Metab. 313:E608–E612. DOI:
10.1152/ajpendo.00156.2017. PMID:
28765272.

18. Korean Society for the Study of Obesity. 2022. Clinical practice guidelines for obesity 2022. 8th ed. Korean Society for the Study of Obesity;Seoul:
19. Di Angelantonio E, Bhupathiraju ShN, et al. Global BMI Mortality Collaboration. 2016; Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet. 388:776–786. DOI:
10.1016/S0140-6736(16)30175-1. PMID:
27423262.

20. Beechy L, Galpern J, Petrone A, Das SK. 2012; Assessment tools in obesity-psychological measures, diet, activity, and body composition. Physiol Behav. 107:154–171. DOI:
10.1016/j.physbeh.2012.04.013. PMID:
22548766. PMCID:
PMC7174029.

21. Słowik J, Grochowska-Niedworok E, Maciejewska-Paszek I, et al. 2019; Nutritional status assessment in children and adolescents with various levels of physical activity in aspect of obesity. Obes Facts. 12:554–563. DOI:
10.1159/000502698. PMID:
31639803. PMCID:
PMC6876601.

22. Huang K, Zhao L, Fang H, et al. 2022; A preliminary study on a form of the 24-h recall that balances survey cost and accuracy, based on the NCI Method. Nutrients. 14:2740. DOI:
10.3390/nu14132740. PMID:
35807917. PMCID:
PMC9269212.

24. Ham SJ, Kim DW. 2021; Estimation of the usual food intake distribution reflecting the consumption frequency and a comparison of the proportion of non-consumers: based on the KNHANES 2009. Korean J Community Nutr. 26:296–306. DOI:
10.5720/kjcn.2021.26.4.296.

26. American College of Cardiology/American Heart Association Task Force on Practice Guidelines, Obesity Expert Panel, 2013. 2014; Expert panel report: guidelines (2013) for the management of overweight and obesity in adults. Obesity (Silver Spring). 22 Suppl 2:S41–S410. DOI:
10.1002/oby.20660.
27. Muscogiuri G, El Ghoch M, Colao A, et al. 2021; European guidelines for obesity management in adults with a very low-calorie ketogenic diet: a systematic review and meta-analysis. Obes Facts. 14:222–245. DOI:
10.1159/000515381. PMID:
33882506. PMCID:
PMC8138199.

29. Franz MJ, VanWormer JJ, Crain AL, et al. 2007; Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. J Am Diet Assoc. 107:1755–1767. DOI:
10.1016/j.jada.2007.07.017. PMID:
17904936.

30. Rynders CA, Thomas EA, Zaman A, Pan Z, Catenacci VA, Melanson EL. 2019; Effectiveness of intermittent fasting and time-restricted feeding compared to continuous energy restriction for weight loss. Nutrients. 11:2442. DOI:
10.3390/nu11102442. PMID:
31614992. PMCID:
PMC6836017.

31. Schwingshackl L, Zähringer J, Nitschke K, et al. 2021; Impact of intermittent energy restriction on anthropometric outcomes and intermediate disease markers in patients with overweight and obesity: systematic review and meta-analyses. Crit Rev Food Sci Nutr. 61:1293–1304. DOI:
10.1080/10408398.2020.1757616. PMID:
32363896.

34. Rolls BJ, Roe LS, Beach AM, Kris-Etherton PM. 2005; Provision of foods differing in energy density affects long-term weight loss. Obes Res. 13:1052–1060. DOI:
10.1038/oby.2005.123. PMID:
15976148.

35. Rolls BJ. 2017; Dietary energy density: applying behavioural science to weight management. Nutr Bull. 42:246–253. DOI:
10.1111/nbu.12280. PMID:
29151813. PMCID:
PMC5687574.

36. Rho MR. 2015; Dietary intervention strategies to reduce energy intake in diabetes. J Korean Diabetes. 16:43–48. DOI:
10.4093/jkd.2015.16.1.43.

37. Fogelholm M, Anderssen S, Gunnarsdottir I, Lahti-Koski M. 2012; Dietary macronutrients and food consumption as determinants of long-term weight change in adult populations: a systematic literature review. Food Nutr Res. 56:19103. DOI:
10.3402/fnr.v56i0.19103. PMID:
22893781. PMCID:
PMC3418611.

38. Fechner E, Smeets ETHC, Schrauwen P, Mensink RP. 2020; the effects of different degrees of carbohydrate restriction and carbohydrate replacement on cardiometabolic risk markers in humans-A systematic review and meta-analysis. Nutrients. 12:991. DOI:
10.3390/nu12040991. PMID:
32252374. PMCID:
PMC7230871.

40. Leidy HJ, Clifton PM, Astrup A, et al. 2015; The role of protein in weight loss and maintenance. Am J Clin Nutr. 101:1320S–1329S. DOI:
10.3945/ajcn.114.084038. PMID:
25926512.

41. Frost GS, Brynes AE, Bovill-Taylor C, Dornhorst A. 2004; A prospective randomised trial to determine the efficacy of a low glycaemic index diet given in addition to healthy eating and weight loss advice in patients with coronary heart disease. Eur J Clin Nutr. 58:121–127. DOI:
10.1038/sj.ejcn.1601758. PMID:
14679377.

42. Ko GJ, Rhee CM, Kalantar-Zadeh K, Joshi S. 2020; The effects of high-protein diets on kidney health and longevity. J Am Soc Nephrol. 31:1667–1679. DOI:
10.1681/ASN.2020010028. PMID:
32669325. PMCID:
PMC7460905.

43. Zafar MI, Mills KE, Zheng J, et al. 2019; Low-glycemic index diets as an intervention for diabetes: a systematic review and meta-analysis. Am J Clin Nutr. 110:891–902. DOI:
10.1093/ajcn/nqz149. PMID:
31374573.

44. Zambrano AK, Cadena-Ullauri S, Guevara-Ramírez P, et al. 2023; The impact of a very-low-calorie ketogenic diet in the gut microbiota composition in obesity. Nutrients. 15:2728. DOI:
10.3390/nu15122728. PMID:
37375632. PMCID:
PMC10305724.

45. Guarnotta V, Emanuele F, Amodei R, Giordano C. 2022; Very low-calorie ketogenic diet: a potential application in the treatment of hypercortisolism comorbidities. Nutrients. 14:2388. DOI:
10.3390/nu14122388. PMID:
35745118. PMCID:
PMC9228456.

46. Takahara S, Soni S, Maayah ZH, Ferdaoussi M, Dyck JRB. 2022; Ketone therapy for heart failure: current evidence for clinical use. Cardiovasc Res. 118:977–987. DOI:
10.1093/cvr/cvab068. PMID:
33705533.

47. Storoni M, Plant GT. 2015; The therapeutic potential of the ketogenic diet in treating progressive multiple sclerosis. Mult Scler Int. 2015:681289. DOI:
10.1155/2015/681289. PMID:
26839705. PMCID:
PMC4709725.

48. Grochowska K, Przeliorz A. 2022; The effect of the ketogenic diet on the therapy of neurodegenerative diseases and its impact on improving cognitive functions. Dement Geriatr Cogn Dis Extra. 12:100–106. DOI:
10.1159/000524331. PMID:
35950150. PMCID:
PMC9247494.

49. Muscogiuri G, Barrea L, Laudisio D, et al. 2019; The management of very low-calorie ketogenic diet in obesity outpatient clinic: a practical guide. J Transl Med. 17:356. DOI:
10.1186/s12967-019-2104-z. PMID:
31665015. PMCID:
PMC6820992.

50. Goossens C, Weckx R, Derde S, et al. 2021; Altered cholesterol homeostasis in critical illness-induced muscle weakness: effect of exogenous 3-hydroxybutyrate. Crit Care. 25:252. DOI:
10.1186/s13054-021-03688-1. PMID:
34274000. PMCID:
PMC8285799.

51. Caprio M, Infante M, Moriconi E, et al. 2019; Very-low-calorie ketogenic diet (VLCKD) in the management of metabolic diseases: systematic review and consensus statement from the Italian Society of Endocrinology (SIE). J Endocrinol Invest. 42:1365–1386. DOI:
10.1007/s40618-019-01061-2. PMID:
31111407.

52. Padma V. 2014; DASH diet in preventing hypertension. Adv Biol Res. 8:94–96.
53. Svetkey LP, Sacks FM, Obarzanek E, et al. 1999; The DASH Diet, Sodium Intake and Blood Pressure Trial (DASH-sodium): rationale and design. DASH-Sodium Collaborative Research Group. J Am Diet Assoc. 99(8 Suppl):S96–S104. DOI:
10.1016/S0002-8223(99)00423-X. PMID:
10450301.
54. Konikowska K, Bombała W, Szuba A, Różańska D, Regulska-Ilow B. 2023; A high-quality diet, as measured by the DASH score, is associated with a lower risk of metabolic syndrome and visceral obesity. Biomedicines. 11:317. DOI:
10.3390/biomedicines11020317. PMID:
36830853. PMCID:
PMC9953672.

55. Davis C, Bryan J, Hodgson J, Murphy K. 2015; Definition of the mediterranean diet; a literature review. Nutrients. 7:9139–9153. DOI:
10.3390/nu7115459. PMID:
26556369. PMCID:
PMC4663587.

56. Jeong EH, Kim E, Hong CH, et al. 2019; Practicability of six weeks of Korean-style Mediterranean diet for elderly Koreans with high risk for dementia. J Korean Diet Assoc. 25:237–256.
57. Goldstein SP, Zhang F, Forman E, Evans BC. 2016; Using Machine learning to predict dietary lapses from a weight loss program. Ann Behav Med. 50:S23.
58. Goldstein SP. 2018. Comparing effectiveness and user behaviors of two versions of a just-in-time adaptive weight loss smartphone app. Drexel University;Philadelphia:
59. Rabbi M, Pfammatter A, Zhang M, Spring B, Choudhury T. 2015; Automated personalized feedback for physical activity and dietary behavior change with mobile phones: a randomized controlled trial on adults. JMIR Mhealth Uhealth. 3:e42. DOI:
10.2196/mhealth.4160. PMID:
25977197. PMCID:
PMC4812832.

60. Stein N, Brooks K. 2017; A fully automated conversational artificial intelligence for weight loss: longitudinal observational study among overweight and obese adults. JMIR Diabetes. 2:e20. DOI:
10.2196/diabetes.8590. PMID:
30291087. PMCID:
PMC6238835.

61. Zhou M, Fukuoka Y, Mintz Y, et al. 2018; Evaluating Machine learning-based automated personalized daily step goals delivered through a mobile phone app: randomized controlled trial. JMIR Mhealth Uhealth. 6:e28. DOI:
10.2196/mhealth.9117. PMID:
29371177. PMCID:
PMC5806006.

62. Chew HSJ, Ang WHD, Lau Y. 2021; The potential of artificial intelligence in enhancing adult weight loss: a scoping review. Public Health Nutr. 24:1993–2020. DOI:
10.1017/S1368980021000598. PMID:
33592164. PMCID:
PMC8145469.

63. Kolodziejczyk AA, Zheng D, Elinav E. 2019; Diet-microbiota interactions and personalized nutrition. Nat Rev Microbiol. 17:742–753. DOI:
10.1038/s41579-019-0256-8. PMID:
31541197.

65. Ridaura VK, Faith JJ, Rey FE, et al. 2013; Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science. 341:1241214. DOI:
10.1126/science.1241214. PMID:
24009397. PMCID:
PMC3829625.
66. Rudolph A, Hilbert A. 2013; Post-operative behavioural management in bariatric surgery: a systematic review and meta-analysis of randomized controlled trials. Obes Rev. 14:292–302. DOI:
10.1111/obr.12013. PMID:
23294936.

67. Seo MH, Lee WY, Kim SS, et al. 2019; 2018 Korean society for the study of obesity guideline for the management of obesity in Korea. J Obes Metab Syndr. 28:40–45. DOI:
10.7570/jomes.2019.28.1.40. PMID:
31089578. PMCID:
PMC6484940.
