1
|
Wang F, Glenn AJ, Tessier AJ, Mei Z, Haslam DE, Guasch-Ferré M, Tobias DK, Eliassen AH, Manson JE, Clish C, Lee KH, Rimm EB, Wang DD, Sun Q, Liang L, Willett WC, Hu FB. Integration of epidemiological and blood biomarker analysis links haem iron intake to increased type 2 diabetes risk. Nat Metab 2024:10.1038/s42255-024-01109-5. [PMID: 39138340 DOI: 10.1038/s42255-024-01109-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Accepted: 07/12/2024] [Indexed: 08/15/2024]
Abstract
Dietary haem iron intake is linked to an increased risk of type 2 diabetes (T2D), but the underlying plasma biomarkers are not well understood. We analysed data from 204,615 participants (79% females) in three large US cohorts over up to 36 years, examining the associations between iron intake and T2D risk. We also assessed plasma metabolic biomarkers and metabolomic profiles in subsets of 37,544 (82% females) and 9,024 (84% females) participants, respectively. Here we show that haem iron intake but not non-haem iron is associated with a higher T2D risk, with a multivariable-adjusted hazard ratio of 1.26 (95% confidence interval 1.20-1.33; P for trend <0.001) comparing the highest to the lowest quintiles. Haem iron accounts for significant proportions of the T2D risk linked to unprocessed red meat and specific dietary patterns. Increased haem iron intake correlates with unfavourable plasma profiles of insulinaemia, lipids, inflammation and T2D-linked metabolites. We also identify metabolites, including L-valine and uric acid, potentially mediating the haem iron-T2D relationship, highlighting their pivotal role in T2D pathogenesis.
Collapse
Affiliation(s)
- Fenglei Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Andrea J Glenn
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Anne-Julie Tessier
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zhendong Mei
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle E Haslam
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Deirdre K Tobias
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - A Heather Eliassen
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - JoAnn E Manson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Clary Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kyu Ha Lee
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Eric B Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Dong D Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Qi Sun
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Walter C Willett
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| |
Collapse
|
2
|
Tsuruta H, Sugahara S, Kume S. Nutrient quality in dietary therapy for diabetes and diabetic kidney disease. J Diabetes Investig 2024; 15:973-981. [PMID: 38591876 PMCID: PMC11292394 DOI: 10.1111/jdi.14208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 03/17/2024] [Accepted: 03/21/2024] [Indexed: 04/10/2024] Open
Abstract
Dietary therapy is crucial for diabetes care with the aim of preventing the onset and progression of diabetes and its complications. The traditional approach to dietary therapy for diabetes has primarily focused on restricting the intake of the three major nutrients and rigorously controlling blood glucose levels. However, advancements in nutritional science have shown that within the three major nutrients - carbohydrates, proteins and lipids - there exist multiple types, each with distinct impacts on type 2 diabetes and its complications, sometimes even showing conflicting effects. In light of this, the present review shifts its focus from the quantity to the quality of the three major nutrients. It aims to provide an overview of how the differences in nutrient quality can influence onset and progression of type 2 diabetes and diabetic kidney disease, highlighting the diverse effects and, at times, contradictory impacts associated with each nutrient type.
Collapse
Affiliation(s)
- Hiroaki Tsuruta
- Department of MedicineShiga University of Medical ScienceOtsuShigaJapan
| | - Sho Sugahara
- Department of MedicineShiga University of Medical ScienceOtsuShigaJapan
| | - Shinji Kume
- Department of MedicineShiga University of Medical ScienceOtsuShigaJapan
| |
Collapse
|
3
|
da Silva VT, Mateus N, de Freitas V, Fernandes A. Plant-Based Meat Analogues: Exploring Proteins, Fibers and Polyphenolic Compounds as Functional Ingredients for Future Food Solutions. Foods 2024; 13:2303. [PMID: 39063388 PMCID: PMC11275277 DOI: 10.3390/foods13142303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 07/09/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024] Open
Abstract
As the lack of resources required to meet the demands of a growing population is increasingly evident, plant-based diets can be seen as part of the solution, also addressing ethical, environmental, and health concerns. The rise of vegetarian and vegan food regimes is a powerful catalyzer of a transition from animal-based diets to plant-based diets, which foments the need for innovation within the food industry. Vegetables and fruits are a rich source of protein, and bioactive compounds such as dietary fibres and polyphenols and can be used as technological ingredients (e.g., thickening agents, emulsifiers, or colouring agents), while providing health benefits. This review provides insight on the potential of plant-based ingredients as a source of alternative proteins, dietary fibres and antioxidant compounds, and their use for the development of food- and alternative plant-based products. The application of these ingredients on meat analogues and their impact on health, the environment and consumers' acceptance are discussed. Given the current knowledge on meat analogue production, factors like cost, production and texturization techniques, upscaling conditions, sensory attributes and nutritional safety are factors that require further development to fully achieve the full potential of plant-based meat analogues.
Collapse
Affiliation(s)
- Vasco Trincão da Silva
- Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007 Porto, Portugal
| | - Nuno Mateus
- LAQV-REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007 Porto, Portugal
| | - Victor de Freitas
- LAQV-REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007 Porto, Portugal
| | - Ana Fernandes
- LAQV-REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007 Porto, Portugal
| |
Collapse
|
4
|
Givens DI. Animal board invited review: Dietary transition from animal to plant-derived foods: Are there risks to health? Animal 2024; 18:101263. [PMID: 39121724 DOI: 10.1016/j.animal.2024.101263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 07/09/2024] [Accepted: 07/12/2024] [Indexed: 08/12/2024] Open
Abstract
Animal-derived foods (ADFs) are a very varied group of foods, but many are nutrient rich and contain higher quality protein than provided by plant-derived foods such that a simple replacement of ADF protein is likely to lead to a reduction in overall protein quality. In addition, many ADFs are richer in some nutrients than plant-based foods (e.g. Fe, Ca) and these often have a higher bioavailability. ADFs also provide nutrients that plants cannot supply (e.g. vitamin B12) and some provide beneficial health functionality (e.g. hypotensive) which is not explained by traditional nutrition. However, there remains a good health reason to increase the proportion of plant-derived food in many diets to increase the intake of dietary fibre which is often consumed at very sub-optimal levels. It seems logical that the increased plant-derived foods should replace the ADFs that have the least benefit, the greatest risk to health and the highest environmental impact. Processed meat fits these characteristics and should be an initial target for replacement with plant-based based protein-rich foods that additionally provide the necessary nutrients and have high-quality dietary fibre. Processed meat covers a wide range of products including several traditional foods (e.g. sausages) which will make decisions on food replacement challenging. There is therefore an urgent need for research to better define the relative health risks associated with the range of processed meat-based foods. The aim of this review is to examine the evidence on the benefits and risks of this dietary transition including the absolute necessity to consider initial nutrient status before the replacement of ADFs is considered.
Collapse
Affiliation(s)
- D I Givens
- Institute for Food, Nutrition and Health, University of Reading, Earley Gate, Reading RG6 6EU, United Kingdom.
| |
Collapse
|
5
|
Wolever TM, Zurbau A, Koecher K, Au-Yeung F. The Effect of Adding Protein to a Carbohydrate Meal on Postprandial Glucose and Insulin Responses: A Systematic Review and Meta-Analysis of Acute Controlled Feeding Trials. J Nutr 2024:S0022-3166(24)00392-4. [PMID: 39019167 DOI: 10.1016/j.tjnut.2024.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 05/21/2024] [Accepted: 07/10/2024] [Indexed: 07/19/2024] Open
Abstract
BACKGROUND Protein influences acute postprandial glucose and insulin responses, but the effects of dose, protein type, and health status are unknown. OBJECTIVES We aimed to determine the acute effect of adding protein to carbohydrate on postprandial responses and identify effect modifiers. METHODS We searched MEDLINE, EMBASE, and Cochrane databases through 30 July, 2023 for acute, crossover trials comparing acute postprandial responses elicited by carbohydrate-containing test meals with and without added protein in adults without diabetes or with type 2 (T2DM) or type 1 (T1DM) diabetes mellitus. Group data were pooled separately using generic inverse variance with random-effects models and expressed as the ratio of means with 95% confidence interval. Risk of bias and certainty of evidence (Grading of Recommendations Assessment, Development, and Evaluation) were assessed. RESULTS In 154 trial comparisons of animal, dairy, and plant proteins (without diabetes, n = 22, 67, 32, respectively; T2DM, n = 14, 16, 3, respectively), each gram protein per gram available carbohydrate (g/g) reduced the glucose area under the curve (AUC) less in adults with T2DM than in those without diabetes (-10% compared with -50%, P < 0.05) but increased the insulin AUC similarly (+76% compared with +56%). In subjects without diabetes, each g/g of dairy and plant protein reduced glucose AUC by 52% and 55%, respectively, and increased the insulin AUC by 64% and 45%, respectively (all P < 0.05). Animal proteins significantly reduced the glucose AUC by 31% and increased the insulin AUC by 37% (pooled effects) but without a significant dose-response. In adults with T2DM, animal protein reduced the glucose AUC by 13% and increased the insulin AUC by 105%, with no significant dose-response. Dairy protein reduced the glucose AUC by 18% (no dose-response), but each g/g increased the insulin AUC by 34% (P < 0.05). In adults with T1DM, protein increased the glucose AUC by 40% (P < 0.05, n = 5). Data source (reported AUC compared with calculated AUC) and study methodology quality significantly modified some outcomes and contributed to high between-study heterogeneity. CONCLUSIONS In people without diabetes, adding dairy or plant protein to a carbohydrate-containing meal elicits physiologically significant reductions in glucose AUC and increases insulin AUC. Animal protein may slightly reduce the glucose AUC and may increase the insulin AUC. In people with T2DM, protein may not have such large and consistent effects. Further research is needed to determine if the effects of protein differ by health status and protein source. This study was registered at PROSPERO as CRD42022322090.
Collapse
Affiliation(s)
- Thomas Ms Wolever
- INQUIS Clinical Research, Inc., Toronto, Ontario, Canada; Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Ontario, Canada.
| | - Andreea Zurbau
- INQUIS Clinical Research, Inc., Toronto, Ontario, Canada; Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Katie Koecher
- General Mills, Bell Institute of Health & Nutrition, Minneapolis, MN, United States
| | - Fei Au-Yeung
- INQUIS Clinical Research, Inc., Toronto, Ontario, Canada; Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Toronto, Ontario, Canada
| |
Collapse
|
6
|
Bui LP, Pham TT, Wang F, Chai B, Sun Q, Hu FB, Lee KH, Guasch-Ferre M, Willett WC. Planetary Health Diet Index and risk of total and cause-specific mortality in three prospective cohorts. Am J Clin Nutr 2024; 120:80-91. [PMID: 38960579 PMCID: PMC11251201 DOI: 10.1016/j.ajcnut.2024.03.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 03/16/2024] [Accepted: 03/22/2024] [Indexed: 07/05/2024] Open
Abstract
BACKGROUND In 2019, the EAT-Lancet Commission proposed a healthy dietary pattern that, along with reductions in food waste and improved agricultural practices, could feed the increasing global population sustainably. We developed a Planetary Health Diet Index (PHDI) to quantify adherence to the EAT-Lancet reference diet. OBJECTIVES We aimed to assess associations between PHDI and total and cause-specific mortality in 3 prospective cohorts of males and females in the United States. METHODS We followed 66,692 females from the Nurses' Health Study (1986-2019), 92,438 females from the Nurses' Health Study II (1989-2019), and 47,274 males from the Health Professionals Follow-up Study (1986-2018) who were free of cancer, diabetes, and major cardiovascular diseases at baseline. The PHDI was calculated every 4 y using a semiquantitative food frequency questionnaire. Hazard ratios (HRs) were calculated using multivariable proportional-hazards models. RESULTS During follow-up, we documented 31,330 deaths among females and 23,206 among males. When comparing the highest with the lowest quintile of PHDI, the pooled multivariable-adjusted HRs were 0.77 [95% confidence interval (CI): 0.75, 0.80] for all-cause mortality (P-trend < 0.0001). The PHDI was associated with lower risk of deaths from cardiovascular diseases (HR: 0.86; 95% CI: 0.81, 0.91), cancer (HR: 0.90; 95% CI: 0.85, 0.95), respiratory diseases (HR: 0.53; 95% CI: 0.48, 0.59), and neurodegenerative diseases (HR: 0.72; 95% CI: 0.67, 0.78). In females, but not males, the PHDI was also significantly associated with a lower risk of deaths from infectious diseases (HR: 0.62; 95% CI: 0.51, 0.76). PHDI scores were also associated inversely with greenhouse gas emissions and other environmental impacts. CONCLUSIONS In 3 large United States-based prospective cohorts of males and females with up to 34 y of follow-up, a higher PHDI was associated with lower risk of total and cause-specific mortality and environment impacts.
Collapse
Affiliation(s)
- Linh P Bui
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States; Research Advancement Consortium in Health, Hanoi, Vietnam
| | - Tung T Pham
- Research Advancement Consortium in Health, Hanoi, Vietnam; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States; College of Health Sciences, VinUniversity, Hanoi, Vietnam; Department of Physiology, Hanoi Medical University, Hanoi, Vietnam
| | - Fenglei Wang
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Boyang Chai
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Qi Sun
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Frank B Hu
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Kyu Ha Lee
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States; Department of Biostatistics, Harvard University TH Chan School of Public Health, Boston, MA, United States
| | - Marta Guasch-Ferre
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Department of Public Health and Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Walter C Willett
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States.
| |
Collapse
|
7
|
Kennedy J, Alexander P, Taillie LS, Jaacks LM. Estimated effects of reductions in processed meat consumption and unprocessed red meat consumption on occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the USA: a microsimulation study. Lancet Planet Health 2024; 8:e441-e451. [PMID: 38969472 DOI: 10.1016/s2542-5196(24)00118-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/03/2024] [Accepted: 05/14/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND High consumption of processed meat and unprocessed red meat is associated with increased risk of multiple chronic diseases, although there is substantial uncertainty regarding the relationship for unprocessed red meat. We developed a microsimulation model to estimate how reductions in processed meat and unprocessed red meat consumption could affect rates of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the US adult population. METHODS We used data from two versions of the US National Health and Nutrition Examination Survey, one conducted during 2015-16 and one conducted during 2017-18, to create a simulated US population. The starting cohort was restricted to respondents aged 18 years or older who were not pregnant and had 2 days of dietary-recall data. First, we used previously developed risk models to estimate the baseline disease risk of an individual. For type 2 diabetes we used a logistic-regression model and for cardiovascular disease and colorectal cancer we used Cox proportional-hazard models. We then multiplied baseline risk by relative risk associated with individual processed meat and unprocessed red meat consumption. Prevented occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality were computed by taking the difference between the incidence in the baseline and intervention scenarios. All stages were repeated for ten iterations to correspond to a 10-year time span. Scenarios were reductions of 5%, 10%, 30%, 50%, 75%, and 100% in grams consumed of processed meat, unprocessed red meat, or both. Each scenario was repeated 50 times for uncertainty analysis. FINDINGS The total number of individual respondents included in the simulated population was 8665, representing 242 021 876 US adults. 4493 (51·9%) of 8665 individuals were female and 4172 (48·1%) were male; mean age was 49·54 years (SD 18·38). At baseline, weighted mean daily consumption of processed meat was 29·1 g, with a 30% reduction being 8·7 g per day, and of unprocessed red meat was 46·7 g, with a 30% reduction being 14·0 g per day. We estimated that a 30% reduction in processed meat intake alone could lead to 352 900 (95% uncertainty interval 345 500-359 900) fewer occurrences of type 2 diabetes, 92 500 (85 600-99 900) fewer occurrences of cardiovascular disease, 53 300 (51 400-55 000) fewer occurrences of colorectal cancer, and 16 700 (15 300-17 700) fewer all-cause deaths during the 10-year period. A 30% reduction in unprocessed red meat intake alone could lead to 732 600 (725 700-740 400) fewer occurrences of type 2 diabetes, 291 500 (283 900-298 800) fewer occurrences of cardiovascular disease, 32 200 (31 500-32 700) fewer occurrences of colorectal cancer, and 46 100 (45 300-47 200) fewer all-cause deaths during the 10-year period. A 30% reduction in both processed meat and unprocessed red meat intake could lead to 1 073 400 (1 060 100-1 084 700) fewer occurrences of type 2 diabetes, 382 400 (372 100-391 000) fewer occurrences of cardiovascular disease, 84 400 (82 100-86 200) fewer occurrences of colorectal cancer, and 62 200 (60 600-64 400) fewer all-cause deaths during the 10-year period. INTERPRETATION Reductions in processed meat consumption could reduce the burden of some chronic diseases in the USA. However, more research is needed to increase certainty in the estimated effects of reducing unprocessed red meat consumption. FUNDING The Wellcome Trust.
Collapse
Affiliation(s)
- Joe Kennedy
- Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, UK.
| | - Peter Alexander
- Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, UK; School of Geosciences, University of Edinburgh, Edinburgh, UK
| | - Lindsey Smith Taillie
- Carolina Population Center, Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Lindsay M Jaacks
- Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, UK
| |
Collapse
|
8
|
Perraud E, Wang J, Fouillet H, Mariotti F. In Healthy Pathways of Dietary Changes, a Very Rapid Reduction of Red Meat Is Possible, but Specific Diet Changes Are Required for Full Reduction-A Graph-Based Analysis. J Nutr 2024:S0022-3166(24)00347-X. [PMID: 38914228 DOI: 10.1016/j.tjnut.2024.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 05/31/2024] [Accepted: 06/18/2024] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND Although reducing meat consumption is becoming increasingly popular in Western countries, such a transition to a sustainable diet may pose some nutritional risks. OBJECTIVES We aim to analyze the pathways for reaching a low-meat healthy diet and the changes in other food categories needed to rapidly decrease total red meat consumption. METHODS We used a recently developed method based on graph theory to represent all possible pathways of stepwise changes that avoid nutritional deficiencies toward a target healthy diet. Initial and target diets were defined as the daily consumption of 33 food groups. For each sex, 3 initial diets were taken from the French representative survey third individual and national study on food consumption survey as the mean observed diet and low (first quintile) and high (fifth quintile) meat consumption. Target diets were identified using multicriteria optimization to minimize the long-term health risk (HR) of chronic diseases while ensuring nutritional adequacy. The Dijkstra algorithm was used to identify the optimal pathways between the initial and target diets, with the aim of reducing meat consumption as quickly as possible and thus minimizing long-term HRs. RESULTS Unprocessed red meat was easily minimized in the first steps of the pathways regardless of sex and initial level of meat consumption. However, processed meat could only be decreased later and required prior changes such as increases in fruit, vegetables, and oily fish. During total red meat minimization in females, securing adequate intakes of bioavailable iron had the most substantial impact on the other dietary changes needed. CONCLUSIONS Immediate reduction of red meat consumption is possible on the pathway to a healthy diet that avoids any nutrient deficiency. However, early increases in fruit, vegetables, and fish are required before minimizing total red meat early in the diet.
Collapse
Affiliation(s)
- Elie Perraud
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Palaiseau, France
| | - Juhui Wang
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Palaiseau, France
| | - Hélène Fouillet
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Palaiseau, France
| | - François Mariotti
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Palaiseau, France.
| |
Collapse
|
9
|
Locatelli NT, Chen GFN, Batista MF, Furlan JM, Wagner R, Bandoni DH, de Rosso VV. Nutrition classification schemes for plant-based meat analogues: Drivers to assess nutritional quality and identity profile. Curr Res Food Sci 2024; 9:100796. [PMID: 39021609 PMCID: PMC467084 DOI: 10.1016/j.crfs.2024.100796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 06/10/2024] [Accepted: 06/17/2024] [Indexed: 07/20/2024] Open
Abstract
Changes in dietary patterns promoted by the emergence of alternative food systems are becoming increasingly common. The decrease in the consumption of animal-derived products promoted exponential growth in plant-based product demand and, consequently, the availability of several meat analogues for this consumer market. Plant-based meat analogues (PBMAs) were developed to mimic the physical and sensory characteristics of meats and their derivatives. Therefore, the composition of these products has been studied in some countries as an attempt to evaluate their nutritional quality in comparison with that of traditional meat products. The main aim of this study was to employ different Nutrition Classification Schemes (NCSs) to assess the nutritional quality of plant-based meat and to discuss the application of one or more NCSs in defining the identity and quality profile of these foods. Five NCSs were used: three nutrient-based (Nutri-Score; Nutrient Profiling Model (NPM) from Brazil; NPM from PAHO); one food-based (NOVA classification); and one hybrid (Plant-Based Nutrient Profile Model). The nutritional composition and ingredients were collected from labels of 349 PBMAs; 117 were classified as burgers, and 182 products employed soy as the main protein ingredient. The use of different NCSs is strategic for PBMAs' nutritional quality evaluation, and the Nutri-Score was able to show the effectiveness of differentiating products as having poor nutritional quality. In this way, the employment of NPM from Brazil is recommended as a driver for PBMAs choices, especially due to the excellent agreement between the Nutri-Score and NPM from Brazil for burgers.
Collapse
Affiliation(s)
- Nathalia Tarossi Locatelli
- Food Labeling Observatory, Nutrition and Food Service Research Center (CPPNAC), Federal University of São Paulo (UNIFESP), Santos, SP, Brazil
- Graduate Program in Nutrition, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | - Grace Fen Ning Chen
- Food Labeling Observatory, Nutrition and Food Service Research Center (CPPNAC), Federal University of São Paulo (UNIFESP), Santos, SP, Brazil
| | - Mariana Frazão Batista
- Food Labeling Observatory, Nutrition and Food Service Research Center (CPPNAC), Federal University of São Paulo (UNIFESP), Santos, SP, Brazil
- Graduate Program in Nutrition, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | | | - Roger Wagner
- Department of Technology and Food Science, Federal University of Santa Maria (UFSM), Santa Maria, Rio Grande do Sul, Brazil
| | - Daniel Henrique Bandoni
- Food Labeling Observatory, Nutrition and Food Service Research Center (CPPNAC), Federal University of São Paulo (UNIFESP), Santos, SP, Brazil
| | - Veridiana Vera de Rosso
- Food Labeling Observatory, Nutrition and Food Service Research Center (CPPNAC), Federal University of São Paulo (UNIFESP), Santos, SP, Brazil
| |
Collapse
|
10
|
Feraco A, Armani A, Amoah I, Guseva E, Camajani E, Gorini S, Strollo R, Padua E, Caprio M, Lombardo M. Assessing gender differences in food preferences and physical activity: a population-based survey. Front Nutr 2024; 11:1348456. [PMID: 38445208 PMCID: PMC10912473 DOI: 10.3389/fnut.2024.1348456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/12/2024] [Indexed: 03/07/2024] Open
Abstract
Introduction Food preferences are influenced by various factors, such as culture, age, and gender. The relationship between food tastes, meal preferences, and eating habits has been studied extensively in recent years; however, research on gender differences in these fields still needs to be addressed. The aim of this study was to investigate gender differences in food preferences and eating habits through self-administered questionnaires in a large Italian population sample. Methods The online survey included questions on food tastes, meal preferences, eating habits, and sport involvement. Results The results of the study underline significant gender-specific dietary tendencies among the 2198 participants (1314 females and 884 males, average age 41.1 ± 12.7 yrs). The majority of subjects were in the annual income range between €20,000 and €40,000. Our analysis reveals significant gender differences in dietary preferences and eating habits. Men prefer red and processed meat, with significantly higher consumption rates than women. Women, on the other hand, show a greater inclination towards vegetables, whole grains, tofu, and high-cocoa-content dark chocolate, aligning with healthier food choices. The study also found differences in eating behaviors, including the frequency of meals, snacking habits, and hunger patterns: women tend to eat more frequently and report higher levels of hunger in the morning, while men tend to skip snacks. Furthermore, differences extend to eating contexts, such as the speed of eating, eating out, and eating alone, with men more likely to eat quickly and dine out. Episodes of uncontrolled eating without hunger also differ, with women reporting these behaviors more frequently than men. In addition, the analysis of sports preferences showed distinct patterns, with a lower percentage of women playing sports and those who do play sports preferring endurance and strength training, while men prefer strength training and endurance sports. Discussion These findings elucidate the complex interplay of biological, cultural, and gender-based factors in shaping dietary preferences and eating behaviors. In particular, our study reveals that gender dynamics significantly influence food choice and eating habits: women tend to choose healthier foods and eat regular meals, while men show preferences for specific tastes and meal-related behaviors. This analysis underscores the nuanced differences between male and female dietary patterns, influenced not only by inherent biological factors such as genetics and hormonal responses but also by societal norms and cultural contexts. Taken together, our results highlight the importance of integrating different perspectives, thus providing valuable insights into the development of public health strategies and tailored nutrition interventions aimed at chronic disease prevention.
Collapse
Affiliation(s)
- Alessandra Feraco
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
- Laboratory of Cardiovascular Endocrinology, San Raffaele Research Institute, IRCCS San Raffaele Roma, Rome, Italy
| | - Andrea Armani
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
- Laboratory of Cardiovascular Endocrinology, San Raffaele Research Institute, IRCCS San Raffaele Roma, Rome, Italy
| | - Isaac Amoah
- Department of Biochemistry and Biotechnology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Elena Guseva
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
| | - Elisabetta Camajani
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
- Laboratory of Cardiovascular Endocrinology, San Raffaele Research Institute, IRCCS San Raffaele Roma, Rome, Italy
| | - Stefania Gorini
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
- Laboratory of Cardiovascular Endocrinology, San Raffaele Research Institute, IRCCS San Raffaele Roma, Rome, Italy
| | - Rocky Strollo
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
| | - Elvira Padua
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
| | - Massimiliano Caprio
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
- Laboratory of Cardiovascular Endocrinology, San Raffaele Research Institute, IRCCS San Raffaele Roma, Rome, Italy
| | - Mauro Lombardo
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, Rome, Italy
| |
Collapse
|
11
|
Kremer D. Red meat and type 2 diabetes: do methodological advancements sufficiently increase the certainty of evidence? Am J Clin Nutr 2023; 118:1075-1076. [PMID: 37865183 DOI: 10.1016/j.ajcnut.2023.09.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 09/27/2023] [Accepted: 09/27/2023] [Indexed: 10/23/2023] Open
Affiliation(s)
- Daan Kremer
- Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| |
Collapse
|