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Balasubramanian R, Schneider E, Gunnigle E, Cotter PD, Cryan JF. Fermented foods: Harnessing their potential to modulate the microbiota-gut-brain axis for mental health. Neurosci Biobehav Rev 2024; 158:105562. [PMID: 38278378 DOI: 10.1016/j.neubiorev.2024.105562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/18/2024] [Accepted: 01/21/2024] [Indexed: 01/28/2024]
Abstract
Over the past two decades, whole food supplementation strategies have been leveraged to target mental health. In addition, there has been increasing attention on the ability of gut microbes, so called psychobiotics, to positively impact behaviour though the microbiota-gut-brain axis. Fermented foods offer themselves as a combined whole food microbiota modulating intervention. Indeed, they contain potentially beneficial microbes, microbial metabolites and other bioactives, which are being harnessed to target the microbiota-gut-brain axis for positive benefits. This review highlights the diverse nature of fermented foods in terms of the raw materials used and type of fermentation employed, and summarises their potential to shape composition of the gut microbiota, the gut to brain communication pathways including the immune system and, ultimately, modulate the microbiota-gut-brain axis. Throughout, we identify knowledge gaps and challenges faced in designing human studies for investigating the mental health-promoting potential of individual fermented foods or components thereof. Importantly, we also suggest solutions that can advance understanding of the therapeutic merit of fermented foods to modulate the microbiota-gut-brain axis.
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Affiliation(s)
- Ramya Balasubramanian
- APC Microbiome Ireland, University College Cork, Cork, Ireland; Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland; Food Biosciences Department, Teagasc Food Research Centre, Moorepark, Fermoy, P61C996, County Cork, Ireland
| | | | - Eoin Gunnigle
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Paul D Cotter
- APC Microbiome Ireland, University College Cork, Cork, Ireland; Food Biosciences Department, Teagasc Food Research Centre, Moorepark, Fermoy, P61C996, County Cork, Ireland.
| | - John F Cryan
- APC Microbiome Ireland, University College Cork, Cork, Ireland; Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland.
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Casey JL, Meijer JL, IglayReger HB, Ball SC, Han-Markey TL, Braun TM, Burant CF, Peterson KE. Comparing Self-Reported Dietary Intake to Provided Diet during a Randomized Controlled Feeding Intervention: A Pilot Study. DIETETICS (BASEL, SWITZERLAND) 2023; 2:334-343. [PMID: 38107624 PMCID: PMC10722558 DOI: 10.3390/dietetics2040024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Systematic and random errors based on self-reported diet may bias estimates of dietary intake. The objective of this pilot study was to describe errors in self-reported dietary intake by comparing 24 h dietary recalls to provided menu items in a controlled feeding study. This feeding study was a parallel randomized block design consisting of a standard diet (STD; 15% protein, 50% carbohydrate, 35% fat) followed by either a high-fat (HF; 15% protein, 25% carbohydrate, 60% fat) or a high-carbohydrate (HC; 15% protein, 75% carbohydrate, 10% fat) diet. During the intervention, participants reported dietary intake in 24 h recalls. Participants included 12 males (seven HC, five HF) and 12 females (six HC, six HF). The Nutrition Data System for Research was utilized to quantify energy, macronutrients, and serving size of food groups. Statistical analyses assessed differences in 24 h dietary recalls vs. provided menu items, considering intervention type (STD vs. HF vs. HC) (Student's t-test). Caloric intake was consistent between self-reported intake and provided meals. Participants in the HF diet underreported energy-adjusted dietary fat and participants in the HC diet underreported energy-adjusted dietary carbohydrates. Energy-adjusted protein intake was overreported in each dietary intervention, specifically overreporting beef and poultry. Classifying misreported dietary components can lead to strategies to mitigate self-report errors for accurate dietary assessment.
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Affiliation(s)
- James L. Casey
- Department of Nutritional Sciences, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer L. Meijer
- Department of Nutritional Sciences, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH 03756, USA
- Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
| | - Heidi B. IglayReger
- Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sarah C. Ball
- Department of Nutritional Sciences, University of Michigan, Ann Arbor, MI 48109, USA
| | - Theresa L. Han-Markey
- Department of Nutritional Sciences, University of Michigan, Ann Arbor, MI 48109, USA
| | - Thomas M. Braun
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Charles F. Burant
- Department of Nutritional Sciences, University of Michigan, Ann Arbor, MI 48109, USA
- Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Karen E. Peterson
- Department of Nutritional Sciences, University of Michigan, Ann Arbor, MI 48109, USA
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Zimmer M, Obbagy J, Scanlon KS, Gibbs K, Lerman JL, Hamner HC, Pannucci T, Sharfman A, Reedy J, Herrick KA. Count Every Bite to Make "Every Bite Count": Measurement Gaps and Future Directions for Assessing Diet From Birth to 24 Months. J Acad Nutr Diet 2023; 123:1269-1279.e1. [PMID: 37196980 PMCID: PMC10809843 DOI: 10.1016/j.jand.2023.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 04/01/2023] [Accepted: 05/09/2023] [Indexed: 05/19/2023]
Affiliation(s)
- Meghan Zimmer
- Harvard University, Cambridge, Massachusetts; U.S. Department of Health and Human Services, National Cancer Institute, Bethesda, MD
| | - Julie Obbagy
- Food and Nutrition Service, USDA, Alexandria, Virginia
| | - Kelley S Scanlon
- Supplemental Nutrition and Safety Research and Analysis Division, Office of Policy Support, USDA Food and Nutrition Service, Alexandria, Virginia
| | - Kimberlea Gibbs
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland
| | - Jennifer L Lerman
- U.S. Department of Health and Human Services, National Cancer Institute, Bethesda, MD
| | | | | | | | - Jill Reedy
- U.S. Department of Health and Human Services, National Cancer Institute, Bethesda, MD
| | - Kirsten A Herrick
- U.S. Department of Health and Human Services, National Cancer Institute, Bethesda, MD.
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Ramírez-Contreras C, Farran-Codina A, Zerón-Rugerio MF, Izquierdo-Pulido M. Relative Validity and Reliability of the Remind App as an Image-Based Method to Assess Dietary Intake and Meal Timing in Young Adults. Nutrients 2023; 15:nu15081824. [PMID: 37111043 PMCID: PMC10146256 DOI: 10.3390/nu15081824] [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: 03/21/2023] [Revised: 04/03/2023] [Accepted: 04/05/2023] [Indexed: 04/29/2023] Open
Abstract
Image-based dietary records have been validated as tools to evaluate dietary intake. However, to determine meal timing, previous studies have relied primarily on image-based smartphone applications without validation. Noteworthy, the validation process is necessary to determine how accurately a test method measures meal timing compared with a reference method over the same time period. Thus, we aimed to assess the relative validity and reliability of the Remind® app as an image-based method to assess dietary intake and meal timing. For this purpose, 71 young adults (aged 20-33 years, 81.7% women) were recruited for a 3-day cross-sectional study, where they completed a 3-day image-based record using the Remind app (test method) and a 3-day handwritten food record (reference method). The relative validity of the test method versus the reference method was assessed using multiple tests including Bland-Altman, % difference, paired t-test/Wilcoxon signed-rank test, Pearson/Spearman correlation coefficients, and cross-classification. We also evaluated the reliability of the test method using an intra-class correlation (ICC) coefficient. The results showed that, compared to the reference method, the relative validity of the test method was good for assessing energy and macronutrient intake, as well as meal timing. Meanwhile, the relative validity of the test method to assess micronutrient intake was poor (p < 0.05) for some micronutrients (iron, phosphorus, potassium, zinc, vitamins B1, B2, B3, B6, C, and E, and folates) and some food groups (cereals and grains, legumes, tubers, oils, and fats). Regarding the reliability of an image-based method to assess dietary intake and meal timing, results ranged from moderate to excellent (ICC 95% confidence interval [95% CI]: 0.50-1.00) for all nutrients, food groups (except oils and fats, which had low to moderate reliability), and meal timings. Thus, the results obtained in this study provide evidence of the relative validity and reliability of image-based methods to assess dietary intake (energy, macronutrients, and most food groups) and meal timing. These results open up a new framework for chrononutrition, as these methods improve the quality of the data collected and also reduce the burden on users to accurately estimate portion size and the timing of meals.
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Affiliation(s)
- Catalina Ramírez-Contreras
- Department of Nutrition, Food Science and Gastronomy, Food Science Torribera Campus, University of Barcelona, 08921 Barcelona, Spain
- INSA-UB, Nutrition and Food Safety Research Institute, University of Barcelona, 08921 Barcelona, Spain
| | - Andreu Farran-Codina
- Department of Nutrition, Food Science and Gastronomy, Food Science Torribera Campus, University of Barcelona, 08921 Barcelona, Spain
- INSA-UB, Nutrition and Food Safety Research Institute, University of Barcelona, 08921 Barcelona, Spain
| | - María Fernanda Zerón-Rugerio
- Department of Nutrition, Food Science and Gastronomy, Food Science Torribera Campus, University of Barcelona, 08921 Barcelona, Spain
- INSA-UB, Nutrition and Food Safety Research Institute, University of Barcelona, 08921 Barcelona, Spain
- Department of Fundamental and Medical-Surgical Nursing, Faculty of Medicine and Health Sciences, University of Barcelona, 08907 Barcelona, Spain
| | - Maria Izquierdo-Pulido
- Department of Nutrition, Food Science and Gastronomy, Food Science Torribera Campus, University of Barcelona, 08921 Barcelona, Spain
- INSA-UB, Nutrition and Food Safety Research Institute, University of Barcelona, 08921 Barcelona, Spain
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Nieman DC. Multiomics Approach to Precision Sports Nutrition: Limits, Challenges, and Possibilities. Front Nutr 2022; 8:796360. [PMID: 34970584 PMCID: PMC8712338 DOI: 10.3389/fnut.2021.796360] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 11/24/2021] [Indexed: 12/15/2022] Open
Abstract
Most sports nutrition guidelines are based on group average responses and professional opinion. Precision nutrition for athletes aims to improve the individualization of nutrition practices to optimize long-term performance and health. This is a 2-step process that first involves the acquisition of individual-specific, science-based information using a variety of sources including lifestyle and medical histories, dietary assessment, physiological assessments from the performance lab and wearable sensors, and multiomics data from blood, urine, saliva, and stool samples. The second step consists of the delivery of science-based nutrition advice, behavior change support, and the monitoring of health and performance efficacy and benefits relative to cost. Individuals vary widely in the way they respond to exercise and nutritional interventions, and understanding why this metabolic heterogeneity exists is critical for further advances in precision nutrition. Another major challenge is the development of evidence-based individualized nutrition recommendations that are embraced and efficacious for athletes seeking the most effective enhancement of performance, metabolic recovery, and health. At this time precision sports nutrition is an emerging discipline that will require continued technological and scientific advances before this approach becomes accurate and practical for athletes and fitness enthusiasts at the small group or individual level. The costs and scientific challenges appear formidable, but what is already being achieved today in precision nutrition through multiomics and sensor technology seemed impossible just two decades ago.
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Affiliation(s)
- David C Nieman
- North Carolina Research Campus, Human Performance Laboratory, Department of Biology, Appalachian State University, Boone, NC, United States
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