Background Although some studies suggest a positive association between ultra-processed food (UPF) intake and type 2 diabetes mellitus (T2DM), little is known about the exact shape and risks associated with different units (percentage of g/day, absolute g/day, serving/day) of UPF intake and whether the association is independent of diet quality, total energy intake, and body mass index (BMI).
Methods Prospective studies published through January 2024 were identified by searching PubMed, Embase, and Web of Science. Summary relative risks (RRs) and 95% confidence intervals (CIs) were estimated using random-effects models. A nonlinear dose-response meta-analysis was conducted using restricted cubic spline analysis.
Results After screening 569 publications, a total of 12 prospective cohort studies were included. Comparing the highest vs. lowest categories of intake, summary RR for T2DM risk was 1.48 (95% CI, 1.36 to 1.61). Higher summary RRs were observed among studies from Europe and North America. Among individual UPF subgroups, processed meats (summary RR, 1.34; 95% CI, 1.16 to 1.54) were positively associated, whereas ultra-processed cereals and breads (0.98; 95% CI, 0.97 to 0.99) and packaged savory snacks (0.92; 95% CI, 0.88 to 0.95) were inversely associated. The summary RRs associated with every 10% (of g/day), 100-g/day, and 1-serving/day increase in UPF intake were 1.14 (95% CI, 1.11 to 1.17), 1.05 (95% CI, 1.03 to 1.06), and 1.04 (95% CI, 1.03 to 1.05), respectively. The dose-response curve for absolute g/d intake suggested nonlinearity, showing a steeper risk increase approximately at >300 g/day. The associations persisted after adjustment for diet quality, energy intake, or BMI.
Conclusion Our data suggest that UPF intake increases diabetes risk, with a potential threshold effect at 300 g/day.
The consumption of ultra-processed foods (UPFs) has surged globally, raising significant public health concerns due to their associations with a range of adverse health outcomes. This review aims to elucidate potential health impacts of UPF intake and underscore the importance of considering diet quality when interpreting study findings. UPF group, as classified by the Nova system based on the extent of industrial processing, contains numerous individual food items with a wide spectrum of nutrient profiles, as well as differential quality as reflected by their potential health effects. The quality of a given food may well misalign with the processing levels so that a UPF food can be nutritious and healthful whereas a non-UPF food can be of low quality and excess intake of which may lead to adverse health consequences. The current review argues that it is critical to focus on the nutritional content and quality of foods and their role within the overall dietary pattern rather than only the level of processing. Further research should dissect health effects of diet quality and food processing, investigate the health impacts of ingredients that render the UPF categorization, understand roles of metabolomics and the gut microbiome in mediating and modulating the health effects of food processing, and consider environmental sustainability in UPF studies. Emphasizing nutrient-dense healthful foods and dietary patterns shall remain the pivotal strategy for promoting overall health and preventing chronic diseases.
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Social determinants of health and type 2 diabetes in Asia Kyunghun Sung, Seung‐Hwan Lee Journal of Diabetes Investigation.2025;[Epub] CrossRef
Background The effects of excessive ultra-processed food (UPF) consumption on body composition measures or sociodemographic disparities are understudied in Korea. We aimed to investigate the association of UPF intake with percent body fat (PBF) and percent appendicular skeletal muscle mass (PASM) by sociodemographic status in adults.
Methods This study used data from the Korea National Health and Nutrition Examination Survey 2008–2011 (n=11,123 aged ≥40 years). We used a NOVA system to classify all foods reported in a 24-hour dietary recall, and the percentage of energy intake (%kcal) from UPFs was estimated. PBF and PASM were measured by dual-energy X-ray absorptiometry. Tertile (T) 3 of PBF indicated adiposity and T1 of PASM indicated low skeletal muscle mass, respectively. Multinomial logistic regression models were used to estimate odds ratios (OR) with 95% confidence interval (CI) after adjusting covariates.
Results UPF intake was positively associated with PBF-defined adiposity (ORper 10% increase, 1.04; 95% CI, 1.002 to 1.08) and low PASM (ORper 10% increase, 1.05; 95% CI, 1.01 to 1.09). These associations were stronger in rural residents (PBF: ORper 10% increase, 1.14; 95% CI, 1.06 to 1.23; PASM: ORper 10% increase, 1.15; 95% CI, 1.07 to 1.23) and not college graduates (PBF: ORper 10% increase, 1.06; 95% CI, 1.02 to 1.11; PASM: ORper 10% increase, 1.07; 95% CI, 1.03 to 1.12) than their counterparts.
Conclusion A higher UPF intake was associated with higher adiposity and lower skeletal muscle mass among Korean adults aged 40 years and older, particularly in those from rural areas and with lower education levels.
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