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).

It is unknown whether the association between ultra-processed food (UPF) intake and type 2 diabetes mellitus differs from other degrees of food processing. We examined the association between degree of food processing and incident type 2 diabetes mellitus. This was a prospective cohort analysis of the European Prospective Investigation into Cancer and Nutrition (EPIC). Dietary intake was assessed at baseline using dietary questionnaires and classified according to the Nova classification into unprocessed/minimally processed food (MPF), processed culinary ingredients (PCI), processed food (PF) and UPF. Type 2 diabetes mellitus cases were verified through multiple methods. Cox regression and statistical substitution analysis was used to estimate associations between MPF + PCI, PF and UPF intake and incident type 2 diabetes mellitus. To investigate heterogeneity in the association between UPF and incident type 2 diabetes mellitus, UPF sub-group analysis was conducted. Different reference groups were used in each analysis. Over an average 10.9 years follow-up of 311,892 individuals, 14,236 type 2 diabetes mellitus cases were identified. Each 10% increment of total daily food intake from UPF (%g/day) was associated with 17% (95% confidence interval (95%CI): 1.14-1.19) higher incident type 2 diabetes mellitus. Each 10% increment in MPF + PCI or PF intake was associated with lower incident type 2 diabetes mellitus (MPF + PCI hazard ratio: 0.94 (95%CI: 0.92-0.96); PF hazard ratio: 0.92 (95%CI: 0.89-0.95)). Replacing UPF with MPF + PCI or PF was associated with lower incident type 2 diabetes mellitus. However, heterogeneity was observed across UPF sub-groups, with breads, biscuits and breakfast cereals, sweets and desserts, and plant-based alternatives associated with lower incident type 2 diabetes mellitus. These findings support recommendations to focus on reducing intake of specific UPF for lowering type 2 diabetes mellitus risk. International Agency for Research on Cancer.

Dicken SJ ，Dahm CC ，Ibsen DB ，Olsen A ，Tjønneland A ，Louati-Hajji M ，Cadeau C ，Marques C ，Schulze MB ，Jannasch F ，Baldassari I ，Manfredi L ，Santucci de Magistris M ，Sánchez 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 ... -  《-》

Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing.

Epidemiological studies have demonstrated an association between the degree of food processing in our diet and the risk of various chronic diseases. Much of this evidence is based on the international Nova classification system, which classifies food into four groups based on the type of processing: (1) Unprocessed and minimally processed foods, (2) Processed culinary ingredients, (3) Processed foods, and (4) "Ultra-processed" foods (UPF). The ability of the Nova classification to accurately characterise the degree of food processing across consumption patterns in various European populations has not been investigated so far. Therefore, we applied the Nova coding to data from the European Prospective Investigation into Cancer and Nutrition (EPIC) in order to characterize the degree of food processing in our diet across European populations with diverse cultural and socio-economic backgrounds and to validate this Nova classification through comparison with objective biomarker measurements. After grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25-p75: 58-66] years) were included in the cross-sectional analysis that characterised consumption patterns based on the Nova classification. The consumption of food products classified as different Nova categories were compared to relevant circulating biomarkers denoting food processing, measured in various subsamples (N between 417 and 9,460) within the EPIC cohort via (partial) correlation analyses (unadjusted and adjusted by sex, age, BMI and country). These biomarkers included an industrial transfatty acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during oil hydrogenation and heating) and urinary 4-methyl syringol sulfate (an indicator for the consumption of smoked food and a component of liquid smoke used in UPF). Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid (r = 0.54) and 4-methyl syringol sulfate (r = 0.43). Associations for the other 3 Nova groups with these food processing biomarkers were either inverse or non-significant (e.g., for unprocessed and minimally processed foods these correlations were -0.07 and -0.37 for elaidic acid and 4-methyl syringol sulfate, respectively). These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results suggest that the Nova classification can accurately capture consumption of UPF, reflected by stronger correlations with circulating levels of industrial elaidic acid and a syringol metabolite compared to diets high in minimally processed foods.

Huybrechts I ，Rauber F ，Nicolas G ，Casagrande C ，Kliemann N ，Wedekind R ，Biessy C ，Scalbert A ，Touvier M ，Aleksandrova K ，Jakszyn P ，Skeie G ，Bajracharya R ，Boer JMA ，Borné Y ，Chajes V ，Dahm CC ，Dansero L ，Guevara M ，Heath AK ，Ibsen DB ，Papier K ，Katzke V ，Kyrø C ，Masala G ，Molina-Montes E ，Robinson OJK ，Santiuste de Pablos C ，Schulze MB ，Simeon V ，Sonestedt E ，Tjønneland A ，Tumino R ，van der Schouw YT ，Verschuren WMM ，Vozar B ，Winkvist A ，Gunter MJ ，Monteiro CA ，Millett C ，Levy RB ... -  《Frontiers in Nutrition》

Degree of food processing and breast cancer risk: a prospective study in 9 European countries.

Recent epidemiological studies have suggested a positive association between ultra-processed food consumption and breast cancer risk, although some studies also reported no association. Furthermore, the evidence regarding the associations between intake of food with lower degrees of processing and breast cancer risk is limited. Thus, we investigated the associations between dietary intake by degree of food processing and breast cancer risk, overall and by breast cancer subtypes in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Dietary intake of EPIC participants was assessed via questionnaires at baseline. More than 11,000 food ingredients were classified into four groups of food processing levels using the NOVA classification system: unprocessed/minimally processed (NOVA 1), culinary ingredients (NOVA 2), processed (NOVA 3) and ultra-processed (NOVA 4). Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of breast cancer per standard deviation increase in daily consumption (grams) of foods from each NOVA group. The current analysis included 14,933 breast cancer cases, diagnosed among the 318,686 EPIC female participants, (median follow-up of 14.9 years). No associations were found between breast cancer risk and the level of dietary intake from NOVA 1 [HR per 1 SD=0.99 (95% CI 0.97 - 1.01)], NOVA 2 [HR per 1 SD =1.01 (95% CI 0.98 - 1.03)] and NOVA 4 [HR per 1 SD =1.01 (95% CI 0.99 - 1.03)] foods. However, a positive association was found between NOVA 3 and breast cancer risk [HR per 1 SD =1.05 (95% CI 1.03 - 1.07)] which became non-significant after adjustment for alcohol intake [HR per 1 SD =1.01 (95% CI 0.98 - 1.05)] or when beer and wine were excluded from this group [HR per 1 SD =0.99 (95% CI 0.97 - 1.01)]. The associations did not differ by breast cancer subtype, menopausal status or body mass index. Findings from this large-scale prospective study suggest that the positive association between processed food intake and breast cancer risk was likely driven by alcoholic beverage consumption. The online version contains supplementary material available at 10.1186/s43014-024-00264-2.

Cairat M ，Yammine S ，Fiolet T ，Fournier A ，Boutron-Ruault MC ，Laouali N ，Mancini FR ，Severi G ，Berstein FM ，Rauber F ，Levy RB ，Skeie G ，Borch KB ，Tjønneland A ，Mellemkjær L ，Borné Y ，Rosendahl AH ，Masala G ，Giraudo MT ，de Magistris MS ，Katzke V ，Bajracharya R ，Santiuste C ，Amiano P ，Bodén S ，Castro-Espin C ，Sánchez MJ ，Touvier M ，Deschasaux-Tanguy M ，Srour B ，Schulze MB ，Guevara M ，Kliemann N ，Lopez JB ，Al Nahas A ，Chang K ，Vamos EP ，Millett C ，Riboli E ，Heath AK ，Biessy C ，Viallon V ，Casagrande C ，Nicolas G ，Gunter MJ ，Huybrechts I ... -  《-》

Diabetes as a risk factor for tuberculosis disease.

Franco JV ，Bongaerts B ，Metzendorf MI ，Risso A ，Guo Y ，Peña Silva L ，Boeckmann M ，Schlesinger S ，Damen JA ，Richter B ，Baddeley A ，Bastard M ，Carlqvist A ，Garcia-Casal MN ，Hemmingsen B ，Mavhunga F ，Manne-Goehler J ，Viney K ... -  《Cochrane Database of Systematic Reviews》

Defining the optimum strategy for identifying adults and children with coeliac disease: systematic review and economic modelling.

Elwenspoek MM ，Thom H ，Sheppard AL ，Keeney E ，O'Donnell R ，Jackson J ，Roadevin C ，Dawson S ，Lane D ，Stubbs J ，Everitt H ，Watson JC ，Hay AD ，Gillett P ，Robins G ，Jones HE ，Mallett S ，Whiting PF ... -  《-》