Precision nutrition: A systematic literature review

Kirk, Daniel; Çatal, Çağatay; Tekinerdoğan, Bedir

doi:10.1016/j.compbiomed.2021.104365

Cited by 111 publications

(64 citation statements)

References 91 publications

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“…Collectively, therefore, the future of T2D prevention and treatment is a personalized nutrition, which offers the best dietary suggestions and lifestyle modifications considering the individual features of each subject [129]. Genetics plays an important role in this context due to the fact that some genetic variants may influence the metabolism of ingested foods and, as a consequence, may modulate the effects of diet on insulin resistance and body weight [79].…”

Section: Discussionmentioning

confidence: 99%

Type 2 Diabetes and Dietary Carbohydrate Intake of Adolescents and Young Adults: What Is the Impact of Different Choices?

2021

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Type 2 diabetes mellitus has a high prevalence worldwide, with a rapidly increasing incidence even in youth. Nutrition, dietary macronutrient composition, and in particular dietary carbohydrates play a major role in the development of type 2 diabetes. The aim of this narrative review is to discuss the current evidence on the role of dietary carbohydrates in the prevention and management of type 2 diabetes. The digestibility or availability of carbohydrates and their glycemic index (and glycemic load) markedly influence the glycemic response. High consumption of dietary fiber is beneficial for management of type 2 diabetes, whereas high consumption of both glycemic starch and sugars may have a harmful effect on glucose metabolism, thereby increasing the risk of developing type 2 diabetes in the presence of genetic predisposition or making its glycemic control more difficult to achieve in people with established T2D. Therefore, the same dietary macronutrient may have harmful or beneficial effects on type 2 diabetes mainly depending on the subtypes consumed. Some other factors are involved in glucose metabolism, such as meal composition, gut microbiota and genetics. For this reason, the glycemic response after carbohydrate consumption is not easy to predict in the single individual. Nutrition suggested to subjects with known type 2 diabetes should be always person-centered, considering the individual features of each subject.

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Section: Discussionmentioning

confidence: 99%

Type 2 Diabetes and Dietary Carbohydrate Intake of Adolescents and Young Adults: What Is the Impact of Different Choices?

2021

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“…Precision nutrition is an eHealth research area that depends on the person’s characteristics to deliver nutritional advice [ 8 ]. One prominent research topic in this area is when advice is supported by machine learning models created from several sources of data—e.g., dietary intake (content and time), personal, genetics, nutrigenomics, activity tracking, metabolomics, and anthropometric.…”

Section: Related Workmentioning

confidence: 99%

Multi-Device Nutrition Control

Cunha

Duarte

2022

Sensors

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Precision nutrition is a popular eHealth topic among several groups, such as athletes, people with dementia, rare diseases, diabetes, and overweight. Its implementation demands tight nutrition control, starting with nutritionists who build up food plans for specific groups or individuals. Each person then follows the food plan by preparing meals and logging all food and water intake. However, the discipline demanded to follow food plans and log food intake results in high dropout rates. This article presents the concepts, requirements, and architecture of a solution that assists the nutritionist in building up and revising food plans and the user following them. It does so by minimizing human–computer interaction by integrating the nutritionist and user systems and introducing off-the-shelf IoT devices in the system, such as temperature sensors, smartwatches, smartphones, and smart bottles. An interaction time analysis using the keystroke-level model provides a baseline for comparison in future work addressing both the use of machine learning and IoT devices to reduce the interaction effort of users.

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Section: Personalized and Precision Nutritionmentioning

confidence: 99%

“…A new generation of studies is needed with in depth phenotyping and integration of multiomics data with machine learning (a subbranch of Artificial Intelligence) to aid in the development of predictive precision nutrition models ( 6 , 11 , 15 ). Supervised and unsupervised machine learning algorithms focus on patterns within large and complex precision nutrition datasets to develop maximum likelihood predictions about the outcomes of interest ( 15 ). The use of machine learning in precision nutrition is an emerging discipline, and one of the fundamental challenges is the development of high-quality datasets from large cohorts from which pertinent measurements have been obtained.…”

Section: Personalized and Precision Nutritionmentioning

confidence: 99%

“…The use of machine learning in precision nutrition is an emerging discipline, and one of the fundamental challenges is the development of high-quality datasets from large cohorts from which pertinent measurements have been obtained. Another challenge is the use of evaluation metrics to verify the actual effectiveness of the prediction models ( 15 ).…”

Section: Personalized and Precision Nutritionmentioning

confidence: 99%

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Multiomics Approach to Precision Sports Nutrition: Limits, Challenges, and Possibilities

Nieman

2021

Front. Nutr.

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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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Precision nutrition: A systematic literature review

Cited by 111 publications

References 91 publications

Type 2 Diabetes and Dietary Carbohydrate Intake of Adolescents and Young Adults: What Is the Impact of Different Choices?

Type 2 Diabetes and Dietary Carbohydrate Intake of Adolescents and Young Adults: What Is the Impact of Different Choices?

Multi-Device Nutrition Control

Multiomics Approach to Precision Sports Nutrition: Limits, Challenges, and Possibilities

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