Ultra-processed Food Reducing Intervention and Continuous Glucose Monitoring

NCT ID: NCT07175701

Last Updated: 2025-09-16

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

40 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-10-01

Study Completion Date

2026-08-31

Brief Summary

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The goal of this trial is to investigate whether reduction in ultra-processed food intake through diet counseling and education can improve postprandial glucose levels and glycemic variability among Korean healthy adults aged 20-30 years. The main questions it aims to answer are:

* Does the reduction in ultra-processed food intake lower postprandial glucose levels and glycemic variability in healthy adults without a history of diabetes?
* Does the reduced intake in different ultra-processed food subgroups and items differentially influence postprandial glucose and glycemic variability?
* Does other dietary and lifestyle factors (physical activity, sleep, smoking) alter the association between ultra-processed food intake reduction and glycemic variability?

Participants will:

* Undergo the 10-day pre-intervention monitoring period, during which each participant will wear a continuous glucose monitoring (CGM) device and concurrently report their daily dietary intakes (all food and beverage consumptions) and other lifestyle behaviors (sleep, smoking, physical activity)
* After the 10-day pre-intervention monitoring period, participants will be randomized to either intervention or control group
* Intervention group: Participants will visit the research site to receive dietitian-led nutrition education and personalized diet counseling targeting reduction of ultra-processed food intake, as well as improving diet quality. Personalized diet counseling will be provided by study dietitian based on participant's records of dietary intakes during the 10-day pre-intervention monitoring period.
* Control group: Participants will receive dietitian-led nutrition education and personalized diet counseling targeting general improvement in nutrient intake (based on the national dietary guidelines).
* After the intervention, participants will undergo the 10-day post-intervention monitoring period, during which participants will wear a new CGM device for an additional 10 days and continue daily reporting of dietary intakes (all food and beverage consumptions) and lifestyle behaviors (sleep, smoking, physical activity).

Detailed Description

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Diabetes is one of leading causes of mortality in Korean population. The increasing trend in diabetes prevalence is also observed among young Korean adults aged 19-29 years, imposing a substantial societal and economic burden. To mitigate the burden of diabetes, nutrient-based dietary strategies, such as increasing the intake of dietary fiber, while reducing total energy intake, and the consumption of refined carbohydrates, trans and saturated fats, and sodium, have been widely recommended to improve glycemic control and reduce glucose fluctuations. However, recent studies examining the association between ultra-processed food (UPF) intake and type 2 diabetes have suggested that the degree and methods of food processing may be independently associated with glycemic dysregulation, and this association is not fully considered in current nutrient-based dietary guidelines.

According to the Nova classification, UPFs represents the most highly processed category of foods, including items such as sugar-sweetened beverages, packaged snacks, fast foods, and instant noodles. UPFs are typically characterized by poor nutritional quality (e.g., high in energy density, dietary fat, and sodium; low in dietary fiber and essential micronutrients) along with the use of ingredients not commonly used in household cooking, such as artificial flavorings, emulsifiers, and colorants. Excessive energy intake and nutrient imbalance resulting from UPF intake have been associated with an increased risk of obesity and chronic diseases, including diabetes. However, food additives commonly found in UPFs may also contribute to chronic inflammation, insulin resistance, and gut microbiome imbalances, all of which can promote glycemic dysregulation leading to the development of type 2 diabetes, independently of their nutrient quality. However, some UPFs with modified nutrient profiles, such as reduced saturated fat or added artificial sweeteners, are often considered as 'healthy' under the current nutrient-based dietary guidelines despite their high food additive contents. In Korea, from 1998 to 2018, the contribution of UPFs to total energy intake continuously increased, whereas that of minimally processed foods declined. Despite the increasing trend of UPF intake, evidence from randomized controlled trials (RCT) directly examining its association with glycemic outcomes including postprandial glucose level and glycemic variability remains limited. As dietary and lifestyle factors may act as potential confounders, RCTs are needed to establish a causal relationship.

Additionally, a previous meta-analysis showed that the magnitude of the associations with type 2 diabetes varied across different UPF subgroups, with processed meats and artificially- and sugar-sweetened beverages showing the greatest magnitude of positive associations. The findings of the previous study suggest that not all UPFs are equally harmful and address the limitations of current Nova classification. While the Nova classification provides a useful framework for identifying UPFs based on the methods and degrees of processing, it does not fully capture the heterogeneity within the group, such as differences in nutrient profiles, amount and types of additives, and specific processing techniques.

Continuous glucose monitoring (CGM) devices provide more accurate and real-time glycemic assessment. This study aims to investigate whether reduction in UPF intake can improve postprandial glucose levels (measured 2 hours after meal initiation) and glycemic variability (coefficient of variation \[CV\], standard deviation \[SD\], time in range 70-180 mg/dL \[TIR70-180\], time in range 90-126 mg/dL \[TIR90-126\], time above range \>126 mg/dL \[TAR126\], and time below range \<90 mg/dL \[TBR90\], in healthy adults aged 20-30 years. Glycemic responses under free-living conditions will be assessed using CGM, allowing for detailed observation of glucose fluctuations in response to daily dietary intake. In addition, this study aims to evaluate the potential role of lifestyle behaviors including sleep, smoking, and physical activity as effect modifiers in the association between reduction in UPF intake and glycemic outcomes.

This study is a single-site, individually randomized trial conducted in Seoul, Korea, by the Health Promotion and Chronic Disease Epidemiology Lab at the College of Health Science, Korea University (KU). The study protocol was designed in accordance with the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines. In summary, 40 adults aged 20-30 years, with no personal history of diabetes and whose energy intake from UPFs constitutes 25% or more, will be recruited from the community. Participants will be observed for 10 days to assess baseline (pre-intervention) glucose levels, dietary intake and lifestyle. To ensure rigorous glucose monitoring, all participants will be wearing a CGM device. This will be followed by a dietary education and counselling session. Participants assigned in the control group will receive conventional dietary education based on nutrient-based national dietary guidelines, whereas those in the intervention group will receive education aimed at reducing UPF intake. After the education and counselling sessions, all participants will be observed for an additional 10 days to collect CGM-derived glucose data, dietary intake, and lifestyle in order to evaluate changes compared to the baseline period.

Conditions

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Glycemic Variability Postprandial Glucose Glucose Levels Glucose Level Change Glycemic Control Glucose Hyperglycemias Glucose Intolerance Food Additives

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

PREVENTION

Blinding Strategy

SINGLE

Participants

Study Groups

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Intervention group

Participants will be randomly assigned to the intervention group using block randomization with a 1:1 allocation ratio.

Group Type EXPERIMENTAL

Behavioral: Nutritional education and diet counselling

Intervention Type BEHAVIORAL

All participants will be asked to visit the study site after the 10-day baseline monitoring period. They will receive a 30-minute nutrition education focusing on reducing UPF intake; and personalized counselling session based on their dietary intake observed during the baseline monitoring period.

Participants allocated to the intervention group will receive nutrition education and personalized counselling aimed at reducing ultra-processed food (UPF) intake by encouraging the substitution of UPFs with unprocessed/minimally processed foods, thereby improving overall diet quality. Participants will be educated on the definition of UPFs, how to identify them, practical strategies for reducing UPF intake, UPF-reducing recipes, and the associations between UPF intake and health outcomes. The content related to UPFs was developed based on previous studies exploring the health effects of UPF intake, while the content on diet quality was based on the 2020 Korean Dietary Reference Intakes.

Control group

Participants will be randomly assigned to the control group using block randomization with a 1:1 allocation ratio.

Group Type ACTIVE_COMPARATOR

Conventional nutrition education and diet counseling

Intervention Type BEHAVIORAL

All participants will be asked to visit the study site after the 10-day baseline monitoring period. Participants in the control group will receive a conventional nutrient-based education and personalized diet counseling developed based on the 2020 Korean Dietary Reference Intakes.

Interventions

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Behavioral: Nutritional education and diet counselling

All participants will be asked to visit the study site after the 10-day baseline monitoring period. They will receive a 30-minute nutrition education focusing on reducing UPF intake; and personalized counselling session based on their dietary intake observed during the baseline monitoring period.

Participants allocated to the intervention group will receive nutrition education and personalized counselling aimed at reducing ultra-processed food (UPF) intake by encouraging the substitution of UPFs with unprocessed/minimally processed foods, thereby improving overall diet quality. Participants will be educated on the definition of UPFs, how to identify them, practical strategies for reducing UPF intake, UPF-reducing recipes, and the associations between UPF intake and health outcomes. The content related to UPFs was developed based on previous studies exploring the health effects of UPF intake, while the content on diet quality was based on the 2020 Korean Dietary Reference Intakes.

Intervention Type BEHAVIORAL

Conventional nutrition education and diet counseling

All participants will be asked to visit the study site after the 10-day baseline monitoring period. Participants in the control group will receive a conventional nutrient-based education and personalized diet counseling developed based on the 2020 Korean Dietary Reference Intakes.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

* Individuals whose ultra-processed food intake constitutes 25% or more of their total energy intake
* Individuals who are able to wear a continuous glucose monitoring device
* individuals who are willing to participate in follow-up assessments on a voluntary basis

Exclusion Criteria

* Individuals who have a personal history of diabetes or any glucose-related disorders
* Individuals with a risk of bleeding
* Individuals who have previously experienced side effects from continuous glucose monitoring device or who are unable to use the continuous glucose monitoring device
* Individuals who are unable to maintain continuous follow-up due to plans such as travel
Minimum Eligible Age

20 Years

Maximum Eligible Age

39 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Korean Society of Cardiometabolic Syndrome (funder)

UNKNOWN

Sponsor Role collaborator

Korea University

OTHER

Sponsor Role lead

Responsible Party

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Hannah Oh

Associate Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Hannah Oh, ScD

Role: PRINCIPAL_INVESTIGATOR

Department of Health Policy and Management, Korea University, Seoul, Republic of Korea

Locations

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Health Promotion Lab, College of Health Science, Korea University

Seoul, Seoul, South Korea

Site Status

Countries

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South Korea

Central Contacts

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Yujin Kim, BSN

Role: CONTACT

+82-10-8712-9763

Facility Contacts

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Yujin Kim, BSN

Role: primary

+82-10-8712-9763

References

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Korea National Health and Nutrition Examination Survey (KNHANES): Trend in DIabetes Prevalence (Based on Fasting Blood Glucose or HbA1c). Korea Disease Control and Prevention Agency (KDCA), 2023.

Reference Type BACKGROUND

Healthy Eating Habits for Patients with Diabetes. World Health Organization, 2017.

Reference Type BACKGROUND

Guidelines for Healthy Eating for Disease Management: Diabetes, Hyperlipidemia, and Hypertension (Volume 3). Ministry of Health and Welfare, Republic of Korea, 2013.

Reference Type BACKGROUND

Dicken SJ, Dahm CC, Ibsen DB, Olsen A, Tjonneland A, Louati-Hajji M, Cadeau C, Marques C, Schulze MB, Jannasch F, Baldassari I, Manfredi L, Santucci de Magistris M, Sanchez MJ, Castro-Espin C, Palacios DR, Amiano P, Guevara M, van der Schouw YT, Boer JMA, Verschuren WMM, Sharp SJ, Forouhi NG, Wareham NJ, Vamos EP, Chang K, Vineis P, Heath AK, Gunter MJ, Nicolas G, Weiderpass E, Huybrechts I, Batterham RL. Food consumption by degree of food processing and risk of type 2 diabetes mellitus: a prospective cohort analysis of the European Prospective Investigation into Cancer and Nutrition (EPIC). Lancet Reg Health Eur. 2024 Sep 16;46:101043. doi: 10.1016/j.lanepe.2024.101043. eCollection 2024 Nov.

Reference Type BACKGROUND
PMID: 39529810 (View on PubMed)

Cho Y, Ryu S, Kim R, Shin MJ, Oh H. Ultra-processed Food Intake and Risk of Type 2 Diabetes in Korean Adults. J Nutr. 2024 Jan;154(1):243-251. doi: 10.1016/j.tjnut.2023.11.021. Epub 2023 Nov 24.

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PMID: 38007182 (View on PubMed)

Chen Z, Khandpur N, Desjardins C, Wang L, Monteiro CA, Rossato SL, Fung TT, Manson JE, Willett WC, Rimm EB, Hu FB, Sun Q, Drouin-Chartier JP. Ultra-Processed Food Consumption and Risk of Type 2 Diabetes: Three Large Prospective U.S. Cohort Studies. Diabetes Care. 2023 Jul 1;46(7):1335-1344. doi: 10.2337/dc22-1993.

Reference Type BACKGROUND
PMID: 36854188 (View on PubMed)

Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, Baraldi LG, Jaime PC. Ultra-processed foods: what they are and how to identify them. Public Health Nutr. 2019 Apr;22(5):936-941. doi: 10.1017/S1368980018003762. Epub 2019 Feb 12.

Reference Type BACKGROUND
PMID: 30744710 (View on PubMed)

Martini D, Godos J, Bonaccio M, Vitaglione P, Grosso G. Ultra-Processed Foods and Nutritional Dietary Profile: A Meta-Analysis of Nationally Representative Samples. Nutrients. 2021 Sep 27;13(10):3390. doi: 10.3390/nu13103390.

Reference Type BACKGROUND
PMID: 34684391 (View on PubMed)

Liu J, Steele EM, Li Y, Karageorgou D, Micha R, Monteiro CA, Mozaffarian D. Consumption of Ultraprocessed Foods and Diet Quality Among U.S. Children and Adults. Am J Prev Med. 2022 Feb;62(2):252-264. doi: 10.1016/j.amepre.2021.08.014. Epub 2021 Nov 6.

Reference Type BACKGROUND
PMID: 34753645 (View on PubMed)

Moradi S, Entezari MH, Mohammadi H, Jayedi A, Lazaridi AV, Kermani MAH, Miraghajani M. Ultra-processed food consumption and adult obesity risk: a systematic review and dose-response meta-analysis. Crit Rev Food Sci Nutr. 2023;63(2):249-260. doi: 10.1080/10408398.2021.1946005. Epub 2021 Jun 30.

Reference Type BACKGROUND
PMID: 34190668 (View on PubMed)

Mendoza K, Smith-Warner SA, Rossato SL, Khandpur N, Manson JE, Qi L, Rimm EB, Mukamal KJ, Willett WC, Wang M, Hu FB, Mattei J, Sun Q. Ultra-processed foods and cardiovascular disease: analysis of three large US prospective cohorts and a systematic review and meta-analysis of prospective cohort studies. Lancet Reg Health Am. 2024 Sep 2;37:100859. doi: 10.1016/j.lana.2024.100859. eCollection 2024 Sep.

Reference Type BACKGROUND
PMID: 39286398 (View on PubMed)

Wang M, Du X, Huang W, Xu Y. Ultra-processed Foods Consumption Increases the Risk of Hypertension in Adults: A Systematic Review and Meta-analysis. Am J Hypertens. 2022 Oct 3;35(10):892-901. doi: 10.1093/ajh/hpac069.

Reference Type BACKGROUND
PMID: 35750049 (View on PubMed)

Kim Y, Cho Y, Kim JE, Lee DH, Oh H. Ultra-Processed Food Intake and Risk of Type 2 Diabetes Mellitus: A Dose-Response Meta-Analysis of Prospective Studies. Diabetes Metab J. 2025 Sep;49(5):1064-1074. doi: 10.4093/dmj.2024.0706. Epub 2025 Jun 9.

Reference Type BACKGROUND
PMID: 40490026 (View on PubMed)

Cao Y, Liu H, Qin N, Ren X, Zhu B, Xia X. Impact of food additives on the composition and function of gut microbiota: A review. Trends in Food Science & Technology. 2020;99:295-310. doi: https://doi.org/10.1016/j.tifs.2020.03.006.

Reference Type BACKGROUND

Simmons AL, Schlezinger JJ, Corkey BE. What Are We Putting in Our Food That Is Making Us Fat? Food Additives, Contaminants, and Other Putative Contributors to Obesity. Curr Obes Rep. 2014 Jun 1;3(2):273-85. doi: 10.1007/s13679-014-0094-y.

Reference Type BACKGROUND
PMID: 25045594 (View on PubMed)

Derbyshire E. Are all 'ultra-processed' foods nutritional demons? A commentary and nutritional profiling analysis. Trends in Food Science & Technology. 2019;94:98-104. doi: https://doi.org/10.1016/j.tifs.2019.08.023.

Reference Type BACKGROUND

Jung S, Kim JY, Park S. Eating patterns in Korean adults, 1998-2018: increased energy contribution of ultra-processed foods in main meals and snacks. Eur J Nutr. 2024 Feb;63(1):279-289. doi: 10.1007/s00394-023-03258-x. Epub 2023 Nov 24.

Reference Type BACKGROUND
PMID: 37999737 (View on PubMed)

Chan AW, Boutron I, Hopewell S, Moher D, Schulz KF, Collins GS, Tunn R, Aggarwal R, Berkwits M, Berlin JA, Bhandari N, Butcher NJ, Campbell MK, Chidebe RCW, Elbourne DR, Farmer AJ, Fergusson DA, Golub RM, Goodman SN, Hoffmann TC, Ioannidis JPA, Kahan BC, Knowles RL, Lamb SE, Lewis S, Loder E, Offringa M, Ravaud P, Richards DP, Rockhold FW, Schriger DL, Siegfried NL, Staniszewska S, Taylor RS, Thabane L, Torgerson DJ, Vohra S, White IR, Hrobjartsson A. SPIRIT 2025 statement: updated guideline for protocols of randomised trials. BMJ. 2025 Apr 28;389:e081477. doi: 10.1136/bmj-2024-081477.

Reference Type BACKGROUND
PMID: 40294953 (View on PubMed)

2nd study on application of Dietary reference intakes for Koreans 2020. Ministry of Health and Welfare, The Korean Nutrition Society, 2022.

Reference Type BACKGROUND

Other Identifiers

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2025-2

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

KUIRB-2025-0124

Identifier Type: -

Identifier Source: org_study_id

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