Nutr Res Pract.  2025 Feb;19(1):96-106. 10.4162/nrp.2025.19.1.96.

The mediating effect of the Korean Healthy Eating Index on the relationship between lifestyle patterns and metabolic syndrome in middle-aged Koreans: data from the 2019–2021 Korea National Health and Nutrition Examination Survey

Affiliations
  • 1Department of Food and Nutrition, Wonkwang University, Iksan 54538, Korea
  • 2Institute of Life Science and Natural Resources, Wonkwang University, Iksan 54538, Korea

Abstract

BACKGROUND/OBJECTIVES
Metabolic syndrome (MetS) is closely connected to dietary and lifestyle factors, with diet being one of the primary risk factors for MetS, acting as a key factor in both prevention and management. In this study, we analyzed the mediating effect of the Korean Healthy Eating Index (KHEI) on the relationship between lifestyle patterns and MetS in middle-aged Koreans using data from the 2019–2021 Korea National Health and Nutrition Examination Survey (KNHANES).
SUBJECTS/METHODS
This study examined data from 5,196 adults aged 40–64 yrs who participated in the eighth KNHANES. Data on 5 lifestyle factors—smoking, alcohol consumption, physical activity, sleep duration, and stress perception—were analyzed. The latent class analysis (LCA) was performed using Mplus 8.11, and SPSS PROCESS Macro v4.2 was used for statistical analysis to analyze the mediating effect of the KHEI.
RESULTS
The model categorized lifestyle factors into three into 3 clusters: ‘Low Activity Class,’ ‘Low Activity and Smoking Class,’ and ‘Multiple Risk Class.’ The KHEI mediation analysis showed significant effects: 0.0205 (95% confidence interval [CI], 0.0062–0.0363) in the ‘Low Activity and Smoke Class,’ and 0.0420 (95% CI, 0.0133–0.0726) in the ‘Multiple Risk Class.’ The mediating effect of the KHEI domain “adequacy” was significant in these groups, with effects of 0.0357 (95% CI, 0.0184–00563) and 0.0662 (95% CI, 0.0364–0.6491), for the respective groups. Balance of energy intake was significant in the group with ‘Multiple Risk Class’ (0.0189; 95% CI, 0.0044–0.0378).
CONCLUSION
The results suggest that a healthy diet improves health management and reduces risk factors for MetS. Nonetheless, better strategies for dietary improvement through a detailed analysis of KHEI components are warranted.

Keyword

Metabolic syndrome; mediation analysis; nutrition assessment, life style; middle aged

Figure

  • Fig. 1 Flow chart representing the selection of study participants.KNHANES, Korea National Health and Nutrition Examination Survey; MetS, metabolic syndrome; BMI, body mass index

  • Fig. 2 The mediating effect of healthy eating index in the mediation model chart.KHEI, Korean Healthy Eating Index; MetS, metabolic syndrome.*P < 0.01, **P < 0.001.


Reference

1. Korean Statistical Information Service (KOSIS). Health screening statistics: status of the number of metabolic syndrome risk factors by age and gender 2022 [Internet]. Daejeon: KOSIS;2024. cited 2024 August 22. Available from: https://kosis.kr/statHtml/statHtml.do?orgId=350&tblId=DT_35007_N136&conn_path=I.
2. Alberti KG, Zimmet P, Shaw J. IDF Epidemiology Task Force Consensus Group. The metabolic syndrome--a new worldwide definition. Lancet. 2005; 366:1059–1062. PMID: 16182882.
Article
3. Kim T, Kang H, Kim E. Comparative study of metabolic syndrome indicators according to smoking amount and physical activity level. KSW. 2022; 17:249–255.
Article
4. Im M, Lee YR, Han S, Cho CM. The effects of lifestyle factors on metabolic syndrome among Korean adults. J Korean Acad Community Health Nurs. 2012; 23:13–21.
Article
5. Hall MH, Muldoon MF, Jennings JR, Buysse DJ, Flory JD, Manuck SB. Self-reported sleep duration is associated with the metabolic syndrome in midlife adults. Sleep. 2008; 31:635–643. PMID: 18517034.
Article
6. Jung JW, Shin HC, Park YW, Kim CH, Cheong SY, Sung E. The relationship between metabolic syndrome, stress and depression: among the 35-64 years old clients of comprehensive medical examination center in one university hospital. Korean J Health Promot. 2004; 4:10–17.
7. Strine TW, Okoro CA, Chapman DP, Balluz LS, Ford ES, Ajani UA, Mokdad AH. Health-related quality of life and health risk behaviors among smokers. Am J Prev Med. 2005; 28:182–187. PMID: 15710274.
Article
8. Finch H. A comparison of statistics for assessing model invariance in latent class analysis. Open J Stat. 2015; 5:191–210.
Article
9. Konikowska K, Bombała W, Szuba A, Różańska D, Regulska-Ilow B. Metabolic syndrome is associated with low diet quality assessed by the Healthy Eating Index-2015 (HEI-2015) and low concentrations of high-density lipoprotein cholesterol. Biomedicines. 2022; 10:2487. PMID: 36289749.
Article
10. Shin S, Lee S. Relation between the total diet quality based on Korean Healthy Eating Index and the incidence of metabolic syndrome constituents and metabolic syndrome among a prospective cohort of Korean adults. Korean J Community Nutr. 2020; 25:61–70.
Article
11. Krokstad S, Ding D, Grunseit AC, Sund ER, Holmen TL, Rangul V, Bauman A. Multiple lifestyle behaviours and mortality, findings from a large population-based Norwegian cohort study - the HUNT study. BMC Public Health. 2017; 17:58. PMID: 28068991.
12. Jeon JY, Yoo S, Kim H. Clustering patterns and correlates of multiple health behaviors in middle-aged Koreans with metabolic syndrome. Korea J Health Educ Promot. 2012; 29:93–105.
13. Kaur J. Assessment and screening of the risk factors in metabolic syndrome. Med Sci (Basel). 2014; 2:140–152.
14. Lee M, Ahn HJ, Lee SJ, Kim PJ, Kim C, Lee SH, Sohn JH, Lee JJ. Lifestyle risk behavior and atherosclerotic cardiovascular risk: an analysis using the Korea National Health and Nutrition Examination Survey. PLoS One. 2024; 19:e0307677. PMID: 39208285.
Article
15. Choi J, Yun EK, Byun HM. Identifying patterns of lifestyle behaviours linked to sociodemographic characteristics and health conditions among young adults in South Korea. J Adv Nurs. 2023; 79:2348–2359. PMID: 36762669.
Article
16. Lee JA, Cha YH, Kim SH, Park HS. Impact of combined lifestyle factors on metabolic syndrome in Korean men. J Public Health (Oxf). 2017; 39:82–89. PMID: 26834191.
Article
17. Guembe MJ, Fernandez-Lazaro CI, Sayon-Orea C, Toledo E, Moreno-Iribas C. RIVANA Study Investigators. Risk for cardiovascular disease associated with metabolic syndrome and its components: a 13-year prospective study in the RIVANA cohort. Cardiovasc Diabetol. 2020; 19:195. PMID: 33222691.
Article
18. Yun S, Park S, Yook SM, Kim K, Shim JE, Hwang JY, Oh K. Development of the Korean Healthy Eating Index for adults, based on the Korea National Health and Nutrition Examination Survey. Nutr Res Pract. 2022; 16:233–247. PMID: 35392533.
Article
19. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005; 112:2735–2752. PMID: 16157765.
20. Wang B, Fan Y, Wang X, Zeng X, Zeng S, Jia H, Li Y, Dai C. Influence of lifestyle patterns on depression among adults with diabetes: a mediation effect of dietary inflammatory index. BMC Public Health. 2024; 24:1779. PMID: 38961392.
Article
21. Hur WM. How researchers estimate indirect effect using bootstrapping: the case of simple, multiple, and double mediation. Korean Bus Rev. 2013; 6:43–59.
22. Nagin D. Group-Based Modeling of Development. Cambridge (MA): Harvard University Press;2005.
23. Kim S, Cho S, Nah EH. The patterns of lifestyle, metabolic status, and obesity among hypertensive Korean patients: a latent class analysis. Epidemiol Health. 2020; 42:e2020061. PMID: 32882119.
24. Seol R, Chun JH. Classification of type 2 diabetes incidence risk and the health behavior of the 30-50-year-old Korean adults: latent class analysis. Int J Environ Res Public Health. 2022; 19:16600. PMID: 36554481.
Article
25. Azevedo PS, Polegato BF, Paiva S, Costa N, Santos P, Bazan S, Fernandes AAH, Fabro A, Pires V, Tanni SE, et al. The role of glucose metabolism and insulin resistance in cardiac remodelling induced by cigarette smoke exposure. J Cell Mol Med. 2021; 25:1314–1318. PMID: 33300293.
Article
26. Sun K, Ren M, Liu D, Wang C, Yang C, Yan L. Alcohol consumption and risk of metabolic syndrome: a meta-analysis of prospective studies. Clin Nutr. 2014; 33:596–602. PMID: 24315622.
Article
27. Reutrakul S, Van Cauter E. Sleep influences on obesity, insulin resistance, and risk of type 2 diabetes. Metabolism. 2018; 84:56–66. PMID: 29510179.
Article
28. Tenk J, Mátrai P, Hegyi P, Rostás I, Garami A, Szabó I, Hartmann P, Pétervári E, Czopf L, Hussain A, et al. Perceived stress correlates with visceral obesity and lipid parameters of the metabolic syndrome: a systematic review and meta-analysis. Psychoneuroendocrinology. 2018; 95:63–73. PMID: 29803182.
Article
29. Park YS, Kang SH, Jang SI, Park EC. Association between lifestyle factors and the risk of metabolic syndrome in the South Korea. Sci Rep. 2022; 12:13356. PMID: 35922546.
Article
30. Kowalski CJ, Mrdjenovich AJ. Beware dichotomies. Perspect Biol Med. 2016; 59:517–535. PMID: 28690242.
Article
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