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Héritier H, Allémann C, Balakiriev O, Boulanger V, Carroll SF, Froidevaux N, Hugon G, Jaquet Y, Kebaili D, Riccardi S, Rousseau-Leupin G, Salathé RM, Salzmann T, Singh R, Symul L, Ugurlu-Baud E, de Verteuil P, Salathé M. Food & You: A digital cohort on personalized nutrition. PLOS Digit Health 2023; 2:e0000389. [PMID: 38033170 PMCID: PMC10688868 DOI: 10.1371/journal.pdig.0000389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 10/13/2023] [Indexed: 12/02/2023]
Abstract
Nutrition is a key contributor to health. Recently, several studies have identified associations between factors such as microbiota composition and health-related responses to dietary intake, raising the potential of personalized nutritional recommendations. To further our understanding of personalized nutrition, detailed individual data must be collected from participants in their day-to-day lives. However, this is challenging in conventional studies that require clinical measurements and site visits. So-called digital or remote cohorts allow in situ data collection on a daily basis through mobile applications, online services, and wearable sensors, but they raise questions about study retention and data quality. "Food & You" is a personalized nutrition study implemented as a digital cohort in which participants track food intake, physical activity, gut microbiota, glycemia, and other data for two to four weeks. Here, we describe the study protocol, report on study completion rates, and describe the collected data, focusing on assessing their quality and reliability. Overall, the study collected data from over 1000 participants, including high-resolution data of nutritional intake of more than 46 million kcal collected from 315,126 dishes over 23,335 participant days, 1,470,030 blood glucose measurements, 49,110 survey responses, and 1,024 stool samples for gut microbiota analysis. Retention was high, with over 60% of the enrolled participants completing the study. Various data quality assessment efforts suggest the captured high-resolution nutritional data accurately reflect individual diet patterns, paving the way for digital cohorts as a typical study design for personalized nutrition.
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Affiliation(s)
- Harris Héritier
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Chloé Allémann
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Oleksandr Balakiriev
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Victor Boulanger
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Sean F. Carroll
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Noé Froidevaux
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Germain Hugon
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Yannis Jaquet
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Djilani Kebaili
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Sandra Riccardi
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Geneviève Rousseau-Leupin
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Rahel M. Salathé
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Talia Salzmann
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Rohan Singh
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Laura Symul
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
- Department of Statistics, Stanford University, Stanford, California, United States of America
| | - Elif Ugurlu-Baud
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Peter de Verteuil
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
| | - Marcel Salathé
- Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland
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El Fatouhi D, Héritier H, Allémann C, Malisoux L, Laouali N, Riveline JP, Salathé M, Fagherazzi G. Associations Between Device-Measured Physical Activity and Glycemic Control and Variability Indices Under Free-Living Conditions. Diabetes Technol Ther 2022; 24:167-177. [PMID: 34648353 PMCID: PMC8971971 DOI: 10.1089/dia.2021.0294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Background: Disturbances of glycemic control and large glycemic variability have been associated with increased risk of type 2 diabetes in the general population as well as complications in people with diabetes. Long-term health benefits of physical activity are well documented but less is known about the timing of potential short-term effects on glycemic control and variability in free-living conditions. Materials and Methods: We analyzed data from 85 participants without diabetes from the Food & You digital cohort. During a 2-week follow-up, device-based daily step count was studied in relationship to glycemic control and variability indices using generalized estimating equations. Glycemic indices, evaluated using flash glucose monitoring devices (FreeStyle Libre), included minimum, maximum, mean, standard deviation, and coefficient of variation of daily glucose values, the glucose management indicator, and the approximate area under the sensor glucose curve. Results: We observed that every 1000 steps/day increase in daily step count was associated with a 0.3588 mg/dL (95% confidence interval [CI]: -0.6931 to -0.0245), a 0.0917 mg/dL (95% CI: -0.1793 to -0.0042), and a 0.0022% (95% CI: -0.0043 to -0.0001) decrease in the maximum glucose values, mean glucose, and in the glucose management indicator of the following day, respectively. We did not find any association between daily step count and glycemic indices from the same day. Conclusions: Increasing physical activity level was linked to blunted glycemic excursions during the next day. Because health-related benefits of physical activity can be long to observe, such short-term physiological benefits could serve as personalized feedback to motivate individuals to engage in healthy behaviors.
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Affiliation(s)
- Douae El Fatouhi
- “Exposome, Heredity, Cancer, and Health” Team, Center of Research in Epidemiology and Population Health (CESP), Inserm U1018, Paris-Saclay University, UVSQ, Gustave Roussy, Espace Maurice Tubiana, Villejuif, France
- Address correspondence to: Douae El Fatouhi, MSc, “Exposome, Heredity, Cancer, and Health” Team, Center of Research in Epidemiology and Population Health (CESP), Inserm U1018, Paris-Saclay University, UVSQ, Gustave Roussy, Espace Maurice Tubiana, 114 rue Edouard Vaillant, Villejuif Cedex 94805, France
| | - Harris Héritier
- Digital Epidemiology Laboratory, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Chloé Allémann
- Digital Epidemiology Laboratory, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Laurent Malisoux
- Physical Activity, Sport and Health Research Unit, Department of Population Health, Luxembourg Institute of Health (LIH), Strassen, Luxembourg
| | - Nasser Laouali
- “Exposome, Heredity, Cancer, and Health” Team, Center of Research in Epidemiology and Population Health (CESP), Inserm U1018, Paris-Saclay University, UVSQ, Gustave Roussy, Espace Maurice Tubiana, Villejuif, France
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, Massachusetts, USA
| | - Jean-Pierre Riveline
- Department of Diabetes and Endocrinology, Assistance Publique-Hôpitaux de Paris, Université de Paris, Lariboisière Hospital, Paris, France
- Inserm U1138, Immunity and Metabolism in Diabetes (ImMeDiab Team), Centre de Recherches des Cordeliers, Paris, France
| | - Marcel Salathé
- Digital Epidemiology Laboratory, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Guy Fagherazzi
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health (LIH), Strassen, Luxembourg
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