Ultra-processed food and incident type 2 diabetes: studying the underlying consumption patterns to unravel the health effects of this heterogeneous food category in the prospective Lifelines cohort

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Abstract

Background

The overall consumption of ultra-processed food (UPF) has previously been associated with type 2 diabetes. However, due to the substantial heterogeneity of this food category, in terms of their nutritional composition and product type, it remains unclear whether previous results apply to all underlying consumption patterns of UPF.

Methods

Of 70,421 participants (35–70 years, 58.6% women) from the Lifelines cohort study, dietary intake was assessed with a food frequency questionnaire. UPF was identified according to the NOVA classification. Principal component analysis (PCA) was performed to derive UPF consumption patterns. The associations of UPF and adherence to UPF consumption patterns with incidence of type 2 diabetes were studied with logistic regression analyses adjusted for age, sex, diet quality, energy intake, alcohol intake, physical activity, TV watching time, smoking status, and educational level.

Results

During a median follow-up of 41 months, a 10% increment in UPF consumption was associated with a 25% higher risk of developing type 2 diabetes (1128 cases; OR 1.25 [95% CI 1.16, 1.34]). PCA revealed four habitual UPF consumption patterns. A pattern high in cold savory snacks (OR 1.16 [95% CI 1.09, 1.22]) and a pattern high in warm savory snacks (OR 1.15 [95% CI 1.08, 1.21]) were associated with an increased risk of incident type 2 diabetes; a pattern high in traditional Dutch cuisine was not associated with type 2 diabetes incidence (OR 1.05 [95% CI 0.97, 1.14]), while a pattern high in sweet snacks and pastries was inversely associated with type 2 diabetes incidence (OR 0.82 [95% CI 0.76, 0.89]).

Conclusions

The heterogeneity of UPF as a general food category is reflected by the discrepancy in associations between four distinct UPF consumption patterns and incident type 2 diabetes. For better public health prevention, research is encouraged to further clarify how different UPF consumption patterns are related to type 2 diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12916-021-02200-4.

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Most cited references 51

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WITHDRAWN: Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas, 9th edition

Pouya Saeedi, Inga Petersohn, Paraskevi Salpea … (2019)

To provide global estimates of diabetes prevalence for 2019 and projections for 2030 and 2045.

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Dietary pattern analysis: a new direction in nutritional epidemiology.

Frank Hu (2002)

Recently, dietary pattern analysis has emerged as an alternative and complementary approach to examining the relationship between diet and the risk of chronic diseases. Instead of looking at individual nutrients or foods, pattern analysis examines the effects of overall diet. Conceptually, dietary patterns represent a broader picture of food and nutrient consumption, and may thus be more predictive of disease risk than individual foods or nutrients. Several studies have suggested that dietary patterns derived from factor or cluster analysis predict disease risk or mortality. In addition, there is growing interest in using dietary quality indices to evaluate whether adherence to a certain dietary pattern (e.g. Mediterranean pattern) or current dietary guidelines lowers the risk of disease. In this review, we describe the rationale for studying dietary patterns, and discuss quantitative methods for analysing dietary patterns and their reproducibility and validity, and the available evidence regarding the relationship between major dietary patterns and the risk of cardiovascular disease.

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Ultra-processed foods: what they are and how to identify them

Carlos A. Monteiro, Geoffrey Cannon, Renata B. Levy … (2019)

The present commentary contains a clear and simple guide designed to identify ultra-processed foods. It responds to the growing interest in ultra-processed foods among policy makers, academic researchers, health professionals, journalists and consumers concerned to devise policies, investigate dietary patterns, advise people, prepare media coverage, and when buying food and checking labels in shops or at home. Ultra-processed foods are defined within the NOVA classification system, which groups foods according to the extent and purpose of industrial processing. Processes enabling the manufacture of ultra-processed foods include the fractioning of whole foods into substances, chemical modifications of these substances, assembly of unmodified and modified food substances, frequent use of cosmetic additives and sophisticated packaging. Processes and ingredients used to manufacture ultra-processed foods are designed to create highly profitable (low-cost ingredients, long shelf-life, emphatic branding), convenient (ready-to-consume), hyper-palatable products liable to displace all other NOVA food groups, notably unprocessed or minimally processed foods. A practical way to identify an ultra-processed product is to check to see if its list of ingredients contains at least one item characteristic of the NOVA ultra-processed food group, which is to say, either food substances never or rarely used in kitchens (such as high-fructose corn syrup, hydrogenated or interesterified oils, and hydrolysed proteins), or classes of additives designed to make the final product palatable or more appealing (such as flavours, flavour enhancers, colours, emulsifiers, emulsifying salts, sweeteners, thickeners, and anti-foaming, bulking, carbonating, foaming, gelling and glazing agents).

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Author and article information

Contributors

Ming-Jie Duan: m.duan@umcg.nl

Journal

Journal ID (nlm-ta): BMC Med

Journal ID (iso-abbrev): BMC Med

Title: BMC Medicine

Publisher: BioMed Central (London )

ISSN (Electronic): 1741-7015

Publication date (Electronic): 13 January 2022

Publication date PMC-release: 13 January 2022

Publication date Collection: 2022

Volume: 20

Electronic Location Identifier: 7

Affiliations

[1 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Internal Medicine, Division Nephrology (AA52), , University Medical Center Groningen, ; P.O. Box 30 001, 9700RB Groningen, The Netherlands

[2 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Epidemiology (FA40), , University Medical Center Groningen, ; P.O. Box 30 001, 9700RB Groningen, The Netherlands

[3 ]GRID grid.4830.f, ISNI 0000 0004 0407 1981, Aletta Jacobs School of Public Health, , University of Groningen, ; P.O. Box 716, 9712GH Groningen, The Netherlands

Article

Publisher ID: 2200

DOI: 10.1186/s12916-021-02200-4

PMC ID: 8756643

PubMed ID: 35022060

SO-VID: 25488464-4427-4957-8d63-4b55895763e0

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 30 July 2021

Date accepted : 25 November 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100010665, h2020 marie skłodowska-curie actions;

Award ID: 754425

Award Recipient : Ming-Jie Duan

Custom metadata

ScienceOpen disciplines: Medicine

Keywords: dietary pattern,epidemiology,nutrition,type 2 diabetes,ultra-processed food

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ScienceOpen disciplines: Medicine

Keywords: dietary pattern, epidemiology, nutrition, type 2 diabetes, ultra-processed food

Ultra-processed food and incident type 2 diabetes: studying the underlying consumption patterns to unravel the health effects of this heterogeneous food category in the prospective Lifelines cohort

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Abstract

Background

Methods

Results

Conclusions

Supplementary Information

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China Tropical Medicine

Most cited references 51

WITHDRAWN: Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas, 9th edition

Dietary pattern analysis: a new direction in nutritional epidemiology.

Ultra-processed foods: what they are and how to identify them

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