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Nutrition articles from across Nature Portfolio

Nutrition is the organic process of nourishing or being nourished, including the processes by which an organism assimilates food and uses it for growth and maintenance.

Latest Research and Reviews

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Precision nutrition to reset virus-induced human metabolic reprogramming and dysregulation (HMRD) in long-COVID

  • A. Satyanarayan Naidu
  • Chin-Kun Wang
  • Sreus A. G. Naidu

research paper for nutrition

Effect of vegetable consumption with chewing on postprandial glucose metabolism in healthy young men: a randomised controlled study

  • Kayoko Kamemoto
  • Yusei Tataka
  • Masashi Miyashita

research paper for nutrition

Association of body mass index with long-term outcomes in older adults hospitalized for COVID-19: an observational study

  • Alain Putot
  • Charline Guyot
  • Virginie Van Wymelbeke-Delannoy

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Influence of malting procedure on the isoflavonoid content of soybeans

  • Alan Gasiński
  • Dawid Mikulski
  • Joanna Kawa-Rygielska

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Knowledge and handling practices for raw hen's eggs during purchase, preparation, storage, and consumption: a cross sectional study

  • Mohammed Sabbah
  • Kamal Badrasawi
  • Manal Badrasawi

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Timing and impact of percutaneous endoscopic gastrostomy insertion in patients with amyotrophic lateral sclerosis: a comprehensive analysis

  • Bugyeong Son
  • Seung Hyun Kim


News and Comment

research paper for nutrition

Seafood access in Kiribati

  • Annisa Chand

research paper for nutrition

Metabolic product of excess niacin is linked to increased risk of cardiovascular events

A metabolic product of excess niacin promotes vascular inflammation in preclinical models and is associated with increased rates of major adverse cardiovascular events in humans.

  • Gregory B. Lim

research paper for nutrition

Introducing meat–rice: grain with added muscles beefs up protein

The laboratory-grown food uses rice as a scaffold for cultured meat.

  • Jude Coleman

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‘Blue foods’ to tackle hidden hunger and improve nutrition

Aquatic foods have been overlooked in moves to end food insecurity. That needs to change, says Christopher Golden.

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Ultra-processed foods and cardiovascular disease

In this Comment, we critically examine the association between the increasing consumption of ultra-processed foods and their negative effect on cardiovascular health. We explore the historical evolution of food processing, the Nova food classification and the epidemiological evidence, and highlight the need for urgent public health interventions.

  • Fernanda Rauber
  • Renata Bertazzi Levy

Big data and personalized nutrition: the key evidence gaps

The field of personalized nutrition hypothesizes that ‘big data’ — biological, behavioural, social and environmental — can be leveraged to make more precise and effective dietary recommendations to individuals for improving health outcomes, compared to generic dietary advice. This article describes the research questions that need to be answered to understand whether personalized nutrition brings additional clinical utility.

  • Nicola Guess

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A late eating midpoint is associated with increased risk of diabetic kidney disease: a cross-sectional study based on NHANES 2013–2020

Modifying diet is crucial for diabetes and complication management. Numerous studies have shown that adjusting eating habits to align with the circadian rhythm may positively affect metabolic health. However, ...

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Traditional japanese diet score and the sustainable development goals by a global comparative ecological study

Reducing the environmental impact of the food supply is important for achieving Sustainable Development Goals (SDGs) worldwide. Previously, we developed the Traditional Japanese Diet Score (TJDS) and reported ...

Association between dietary magnesium intake and muscle mass among hypertensive population: evidence from the National Health and Nutrition Examination Survey

Magnesium is critical for musculoskeletal health. Hypertensive patients are at high risk for magnesium deficiency and muscle loss. This study aimed to explore the association between magnesium intake and muscl...

Adult dietary patterns with increased bean consumption are associated with greater overall shortfall nutrient intakes, lower added sugar, improved weight-related outcomes and better diet quality

Limited evidence is available that focuses on beans within American dietary patterns and health. The purpose of this study was to identify commonly consumed adult dietary patterns that included beans and compa...

Validity and reproducibility of the PERSIAN Cohort food frequency questionnaire: assessment of major dietary patterns

Dietary patterns, encompassing an overall view of individuals’ dietary intake, are suggested as a suitable means of assessing nutrition’s role in chronic disease development. The aim of this study was to evalu...

Associations of dietary patterns and longitudinal brain-volume change in Japanese community-dwelling adults: results from the national institute for longevity sciences-longitudinal study of aging

The association of dietary patterns and longitudinal changes in brain volume has rarely been investigated in Japanese individuals. We prospectively investigated this association in middle-aged and older Japane...

Association between serum 25-hydroxyvitamin D and vitamin D dietary supplementation and risk of all-cause and cardiovascular mortality among adults with hypertension

The relationship between vitamin D status and mortality among adults with hypertension remains unclear.

Effect of soy isoflavone supplementation on blood pressure: a meta-analysis of randomized controlled trials

Previous experimental studies have suggested that the consumption of soy isoflavones may have a potential impact on lowering blood pressure. Nevertheless, epidemiological studies have presented conflicting out...

The effects of L-carnitine supplementation on inflammation, oxidative stress, and clinical outcomes in critically Ill patients with sepsis: a randomized, double-blind, controlled trial

Sepsis, a life-threatening organ dysfunction caused by a host’s dysregulated response to infection with an inflammatory process, becomes a real challenge for the healthcare systems. L-carnitine (LC) has antiox...

Metabolic syndrome risk in adult coffee drinkers with the rs301 variant of the LPL gene

Metabolic syndrome (MetS), a cluster of metabolic and cardiovascular risk factors is influenced by environmental, lifestyle, and genetic factors. We explored whether coffee consumption and the rs301 variant of...

Towards objective measurements of habitual dietary intake patterns: comparing NMR metabolomics and food frequency questionnaire data in a population-based cohort

Low-quality, non-diverse diet is a main risk factor for premature death. Accurate measurement of habitual diet is challenging and there is a need for validated objective methods. Blood metabolite patterns refl...

Circulating concentrations of bile acids and prevalent chronic kidney disease among newly diagnosed type 2 diabetes: a cross-sectional study

The relationship between circulating bile acids (BAs) and kidney function among patients with type 2 diabetes is unclear. We aimed to investigate the associations of circulating concentrations of BAs, particul...

Dietary intake and gastrointestinal symptoms are altered in children with Autism Spectrum Disorder: the relative contribution of autism-linked traits

Dietary and gastrointestinal (GI) problems have been frequently reported in autism spectrum disorder (ASD). However, the relative contributions of autism-linked traits to dietary and GI problems in children wi...

The effect of bovine dairy products and their components on the incidence and natural history of infection: a systematic literature review

Dairy products and their components may impact immune function, although the current evidence base has some research gaps. As part of a larger systematic literature review of dairy products/components (includi...

Food sufficiency status and sleep outcomes in older adults: the National Health and Aging Trends Study (NHATS)

Studies investigating the relationship between food insecurity and sleep among older populations are limited. This study aimed to cross-sectionally examine the associations between food sufficiency status and ...

Effects of vitamin D supplementation on liver fibrogenic factors, vitamin D receptor and liver fibrogenic microRNAs in metabolic dysfunction-associated steatotic liver disease (MASLD) patients: an exploratory randomized clinical trial

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global metabolic problem which can lead to irreversible liver fibrosis. It has been shown that vitamin D and its receptors contribute to fi...

Validity of food and nutrient intakes assessed by a food frequency questionnaire among Chinese adults

Studies regarding the validity of the food frequency questionnaire (FFQ) and the food composition table (FCT) are limited in Asian countries. We aimed to evaluate the validity of a 64-item FFQ and different me...

Association of sugar intake from different sources with cardiovascular disease incidence in the prospective cohort of UK Biobank participants

The relation between incident cardiovascular disease (CVD) and sugar might not only depend on the quantity consumed but also on its source. This study aims to assess the association between various sources of ...

Association of dietary inflammatory index and the SARS-CoV-2 infection incidence, severity and mortality of COVID-19: a systematic review and dose-response meta-analysis

Several studies have reported the association between dietary inflammatory index (DII) and the SARS-CoV-2 infection risk, severity or mortality of COVID-19, however, the outcomes remain controversial.

Breakfast quality and its sociodemographic and psychosocial correlates among Italian children, adolescents, and adults from the Italian Nutrition & HEalth Survey (INHES) study

Breakfast quality, together with regularity of breakfast, has been suggested to be associated with cardiometabolic health advantages. We aimed to evaluate the quality of breakfast and its socioeconomic and psy...

The association between lifelines diet score (LLDS) with depression and quality of life in Iranian adolescent girls

It has been proposed that a greater degree of adherence to a healthy dietary pattern is associated with a lower risk of depression and a poor quality of life (QoL). The Lifelines diet score (LLDS) is a new, ev...

Diet in secondary prevention: the effect of dietary patterns on cardiovascular risk factors in patients with cardiovascular disease: a systematic review and network meta-analysis

Improving dietary habits is a first-line recommendation for patients with cardiovascular disease (CVD). It is unclear which dietary pattern most effectively lowers cardiovascular risk factors and what the shor...

Prognostic potential of nutritional risk screening and assessment tools in predicting survival of patients with pancreatic neoplasms: a systematic review

The nutritional evaluation of pancreatic cancer (PC) patients lacks a gold standard or scientific consensus, we aimed to summarize and systematically evaluate the prognostic value of nutritional screening and ...

40 years of adding more fructose to high fructose corn syrup than is safe, through the lens of malabsorption and altered gut health–gateways to chronic disease

Labels do not disclose the excess-free-fructose/unpaired-fructose content in foods/beverages. Objective was to estimate excess-free-fructose intake using USDA loss-adjusted-food-availability (LAFA) data (1970–...

Relationship between trajectories of dietary iron intake and risk of type 2 diabetes mellitus: evidence from a prospective cohort study

The association between dietary iron intake and the risk of type 2 diabetes mellitus (T2DM) remains inconsistent. In this study, we aimed to investigate the relationship between trajectories of dietary iron in...

Dietary pattern and precocious puberty risk in Chinese girls: a case-control study

The role of dietary intake on precocious puberty remains unclear. This study aimed to investigate the association between the amount and frequency of dietary intake and the risk of precocious puberty in Chines...

Tracking progress toward a climate-friendly public food service strategy: assessing nutritional quality and carbon footprint changes in childcare centers

Public food procurement and catering are recognized as important leverage points in promoting sustainable and healthy dietary habits. This study aimed to analyze changes in nutritional quality and carbon footp...

Avocado intake and cardiometabolic risk factors in a representative survey of Australians: a secondary analysis of the 2011–2012 national nutrition and physical activity survey

Avocados are a rich source of nutrients including monounsaturated fats, dietary fibre and phytochemicals. Higher dietary quality is reported in studies of consumers with higher avocado intakes. The present stu...

Components in downstream health promotions to reduce sugar intake among adults: a systematic review

Excessive sugar consumption is well documented as a common risk factor for many Non-Communicable Diseases (NCDs). Thus, an adequate intervention description is important to minimise research waste and improve ...

Improving economic access to healthy diets in first nations communities in high-income, colonised countries: a systematic scoping review

Affordability of healthy food is a key determinant of the diet-related health of First Nations Peoples. This systematic scoping review was commissioned by the Ngaanyatjarra Pitjantjatjara Yankunytjatjara Women...

Associations between estimation of salt intake and salt-restriction spoons and hypertension status in patients with poorly controlled hypertension: a community-based study from Huzhou City, Eastern China

As the prevalence of hypertension increases in China, it is advised to use salt-restriction spoons (SRS) as a lifestyle modification. This study aimed to examine the associations between estimated salt consump...

Potassium levels and the risk of all-cause and cardiovascular mortality among patients with cardiovascular diseases: a meta-analysis of cohort studies

Abnormal blood potassium levels are associated with an increased risk of cardiometabolic diseases and mortality in the general population; however, evidence regarding the association between dyskalemia and mor...

Combined versus independent effects of exercise training and intermittent fasting on body composition and cardiometabolic health in adults: a systematic review and meta-analysis

Exercise training (Ex) and intermittent fasting (IF) are effective for improving body composition and cardiometabolic health overweight and obese adults, but whether combining Ex and IF induces additive or syn...

Correction: Associations Between Plant-Based Dietary Patterns and Risks of Type 2 Diabetes, Cardiovascular Disease, Cancer, and Mortality – A Systematic Review and Meta-analysis

The original article was published in Nutrition Journal 2023 22 :46

The association between hyperuricemia and insulin resistance surrogates, dietary- and lifestyle insulin resistance indices in an Iranian population: MASHAD cohort study

Previous studies have reported insulin resistance (IR) to be associated with hyperuricemia. In this study, we aimed to assess the possible associations between the empirical dietary index for IR (EDIR), the em...

Trends and disparities in prevalence of cardiometabolic diseases by food security status in the United States

Previous studies have demonstrated the association between food security and cardiometabolic diseases (CMDs), yet none have investigated trends in prevalence of CMDs by food security status in the United State...

Effect of nutrition education integrating the health belief model and theory of planned behavior on dietary diversity of pregnant women in Southeast Ethiopia: a cluster randomized controlled trial

Maternal anemia, miscarriage, low birth weight (LBW), preterm birth (PTB), intrauterine growth restriction (IUGR), prenatal and infant mortality, morbidity, and the risk of chronic disease later in life are al...

The effect of diet-induced weight loss on circulating homocysteine levels in people with obesity and type 2 diabetes

Having type 2 diabetes (T2D) in combination with being overweight results in an additional increase in cardiovascular disease (CVD) risk. In addition, T2D and obesity are associated with increased levels of to...

Association of early dietary fiber intake and mortality in septic patients with mechanical ventilation based on MIMIC IV 2.1 database: a cohort study

Whether early dietary fiber intake in septic patients is associated with a better clinical prognosis remains unclear, especially the time and the amount. Therefore, we assessed the association between early di...

Comparison of energy expenditure measurements by a new basic respiratory room vs. classical ventilated hood

Nutritional support is often based on predicted resting energy expenditure (REE). In patients, predictions seem invalid. Indirect calorimetry is the gold standard for measuring EE. For assessments over longer ...

Clusters of carbohydrate-rich foods and associations with type 2 diabetes incidence: a prospective cohort study

About one in ten adults are living with diabetes worldwide. Intake of carbohydrates and carbohydrate-rich foods are often identified as modifiable risk factors for incident type 2 diabetes. However, strong cor...

Interaction between CETP Taq1B polymorphism and dietary patterns on lipid profile and severity of coronary arteries stenosis in patients under coronary angiography: a cross-sectional study

Evidence indicates there are still conflicts regarding CETP Taq1B polymorphism and coronary artery disease risk factors. Current findings about whether dietary patterns can change the relationship of the Taq1B...

The effects of curcumin-piperine supplementation on inflammatory, oxidative stress and metabolic indices in patients with ischemic stroke in the rehabilitation phase: a randomized controlled trial

Stroke is a leading cause of death worldwide, which is associated with a heavy economic and social burden. The purpose of this study was to investigate the effects of supplementation with curcumin-piperine com...

Relationship between dietary carotenoid intake and sleep duration in American adults: a population-based study

To investigate the relationship between dietary carotenoid intake and sleep duration.

Different dietary carbohydrate component intakes and long-term outcomes in patients with NAFLD: results of longitudinal analysis from the UK Biobank

This study aimed to investigate the association between the intake of different dietary carbohydrate components and the long-term outcomes of non-alcoholic fatty liver disease (NAFLD).

Association between frequency of breakfast intake before and during pregnancy and developmental delays in children: the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study

Although an association between maternal nutritional intake and developmental delays in children has been demonstrated, the association of the timing of meal intake and development delays remains unclear. We e...

Development and validation of a novel food exchange system for Chinese pregnant women

The dietary nutritional status of pregnant women is critical for maintaining the health of both mothers and infants. Food exchange systems have been employed in the nutritional guidance of patients in China, a...

Distribution of water turnover by sex and age as estimated by prediction equation in Japanese adolescents and adults: the 2016 National Health and Nutrition Survey, Japan

Although water is essential to the maintenance of health and life, standard values for human water requirements are yet to be determined. This study aimed to evaluate the distribution of water turnover (WT) ac...

Methylmalonic acid, vitamin B12, and mortality risk in patients with preexisting coronary heart disease: a prospective cohort study

The inconsistent relationship between Vitamin B12 (B12), methylmalonic acid (MMA, marker of B12 deficiency) and mortality was poorly understood, especially in patients with coronary heart disease (CHD). This s...

Mushroom consumption and hyperuricemia: results from the National Institute for Longevity Sciences-Longitudinal Study of Aging and the National Health and Nutrition Examination Survey (2007-2018)

Prior study reported that mushroom consumption was associated with a lower incidence of hyperuricemia, but there is limited evidence on this association. We conducted a collaborative study to investigate the a...

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Hazard ratio for obesity was modeled according to mean daily step counts and 25th, 50th, and 75th percentile PRS for body mass index. Shaded regions represent 95% CIs. Model is adjusted for age, sex, mean baseline step counts, cancer status, coronary artery disease status, systolic blood pressure, alcohol use, educational level, and a PRS × mean steps interaction term.

Mean daily steps and polygenic risk score (PRS) for higher body mass index are independently associated with hazard for obesity. Hazard ratios model the difference between the 75th and 25th percentiles for continuous variables. CAD indicate coronary artery disease; and SBP, systolic blood pressure.

Each point estimate is indexed to a hazard ratio for obesity of 1.00 (BMI [calculated as weight in kilograms divided by height in meters squared] ≥30). Error bars represent 95% CIs.

eTable. Cumulative Incidence Estimates of Obesity Based on Polygenic Risk Score for Body Mass Index and Mean Daily Steps at 1, 3, and 5 Years

eFigure 1. CONSORT Diagram

eFigure 2. Risk of Incident Obesity Modeled by Mean Daily Step Count and Polygenic Risk Scores Adjusted for Baseline Body Mass Index

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Brittain EL , Han L , Annis J, et al. Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity. JAMA Netw Open. 2024;7(3):e243821. doi:10.1001/jamanetworkopen.2024.3821

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Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity

  • 1 Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
  • 2 Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
  • 3 Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
  • 4 Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee
  • 5 Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
  • 6 Department of Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
  • 7 Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
  • 8 Department of Biomedical Engineering, Vanderbilt University Medical Center, Nashville, Tennessee
  • 9 Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
  • 10 Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee

Question   Does the degree of physical activity associated with incident obesity vary by genetic risk?

Findings   In this cohort study of 3124 adults, individuals at high genetic risk of obesity needed higher daily step counts to reduce the risk of obesity than those at moderate or low genetic risk.

Meaning   These findings suggest that individualized physical activity recommendations that incorporate genetic background may reduce obesity risk.

Importance   Despite consistent public health recommendations, obesity rates in the US continue to increase. Physical activity recommendations do not account for individual genetic variability, increasing risk of obesity.

Objective   To use activity, clinical, and genetic data from the All of Us Research Program (AoURP) to explore the association of genetic risk of higher body mass index (BMI) with the level of physical activity needed to reduce incident obesity.

Design, Setting, and Participants   In this US population–based retrospective cohort study, participants were enrolled in the AoURP between May 1, 2018, and July 1, 2022. Enrollees in the AoURP who were of European ancestry, owned a personal activity tracking device, and did not have obesity up to 6 months into activity tracking were included in the analysis.

Exposure   Physical activity expressed as daily step counts and a polygenic risk score (PRS) for BMI, calculated as weight in kilograms divided by height in meters squared.

Main Outcome and Measures   Incident obesity (BMI ≥30).

Results   A total of 3124 participants met inclusion criteria. Among 3051 participants with available data, 2216 (73%) were women, and the median age was 52.7 (IQR, 36.4-62.8) years. The total cohort of 3124 participants walked a median of 8326 (IQR, 6499-10 389) steps/d over a median of 5.4 (IQR, 3.4-7.0) years of personal activity tracking. The incidence of obesity over the study period increased from 13% (101 of 781) to 43% (335 of 781) in the lowest and highest PRS quartiles, respectively ( P  = 1.0 × 10 −20 ). The BMI PRS demonstrated an 81% increase in obesity risk ( P  = 3.57 × 10 −20 ) while mean step count demonstrated a 43% reduction ( P  = 5.30 × 10 −12 ) when comparing the 75th and 25th percentiles, respectively. Individuals with a PRS in the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to have a comparable risk of obesity. To have a comparable risk of obesity to individuals at the 25th percentile of PRS, those at the 75th percentile with a baseline BMI of 22 would need to walk an additional 3460 steps/d; with a baseline BMI of 24, an additional 4430 steps/d; with a baseline BMI of 26, an additional 5380 steps/d; and with a baseline BMI of 28, an additional 6350 steps/d.

Conclusions and Relevance   In this cohort study, the association between daily step count and obesity risk across genetic background and baseline BMI were quantified. Population-based recommendations may underestimate physical activity needed to prevent obesity among those at high genetic risk.

In 2000, the World Health Organization declared obesity the greatest threat to the health of Westernized nations. 1 In the US, obesity accounts for over 400 000 deaths per year and affects nearly 40% of the adult population. Despite the modifiable nature of obesity through diet, exercise, and pharmacotherapy, rates have continued to increase.

Physical activity recommendations are a crucial component of public health guidelines for maintaining a healthy weight, with increased physical activity being associated with a reduced risk of obesity. 2 - 4 Fitness trackers and wearable devices have provided an objective means to capture physical activity, and their use may be associated with weight loss. 5 Prior work leveraging these devices has suggested that taking around 8000 steps/d substantially mitigates risk of obesity. 3 , 4 However, current recommendations around physical activity do not take into account other contributors such as caloric intake, energy expenditure, or genetic background, likely leading to less effective prevention of obesity for many people. 6

Obesity has a substantial genetic contribution, with heritability estimates ranging from 40% to 70%. 7 , 8 Prior studies 9 - 11 have shown an inverse association between genetic risk and physical activity with obesity, whereby increasing physical activity can help mitigate higher genetic risk for obesity. These results have implications for physical activity recommendations on an individual level. Most of the prior work 9 - 11 focused on a narrow set of obesity-associated variants or genes and relied on self-reported physical activity, and more recent work using wearable devices has been limited to 7 days of physical activity measurements. 12 Longer-term capture in large populations will be required to accurately estimate differences in physical activity needed to prevent incident obesity.

We used longitudinal activity monitoring and genome sequencing data from the All of Us Research Program (AoURP) to quantify the combined association of genetic risk for body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and physical activity with the risk of incident obesity. Activity monitoring was quantified as daily step counts obtained from fitness tracking devices. Genetic risk was quantified by using a polygenic risk score (PRS) from a large-scale genomewide association study (GWAS) of BMI. 13 We quantified the mean daily step count needed to overcome genetic risk for increased BMI. These findings represent an initial step toward personalized exercise recommendations that integrate genetic information.

Details on the design and execution of the AoURP have been published previously. 14 The present study used AoURP Controlled Tier dataset, version 7 (C2022Q4R9), with data from participants enrolled between May 1, 2018, and July 1, 2022. Participants who provided informed consent could share data from their own activity tracking devices from the time their accounts were first created, which may precede the enrollment date in AoURP. We followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. In this study, only the authorized authors who completed All of Us Responsible Conduct of Research training accessed the deidentified data from the Researcher Workbench (a secured cloud-based platform). Since the authors were not directly involved with the participants, institutional review board review was exempted in compliance with AoURP policy.

Activity tracking data for this study came from the Bring Your Own Device program that allowed individuals who already owned a tracking device (Fitbit, Inc) to consent to link their activity data with other data in the AoURP. By registering their personal device on the AoURP patient portal, patients could share all activity data collected since the creation of their personal device account. For many participants, this allowed us to examine fitness activity data collected prior to enrollment in the AoURP. Activity data in AoURP are reported as daily step counts. We excluded days with fewer than 10 hours of wear time to enrich our cohort for individuals with consistently high wear time. The initial personal activity device cohort consisted of 12 766 individuals. Consistent with our prior data curation approach, days with less than 10 hours of wear time, less than 100 steps, or greater than 45 000 steps or for which the participant was younger than 18 years were removed. For time-varying analyses, mean daily steps were calculated on a monthly basis for each participant. Months with fewer than 15 valid days of monitoring were removed.

The analytic cohort included only individuals with a BMI of less than 30 at the time activity monitoring began. The primary outcome was incident obesity, defined as a BMI of 30 or greater documented in the medical record at least 6 months after initiation of activity monitoring. The latter stipulation reduced the likelihood that having obesity predated the beginning of monitoring but had not yet been clinically documented. We extracted BMI values and clinical characteristics from longitudinal electronic health records (EHRs) for the consenting participants who were associated with a health care provider organization funded by the AoURP. The EHR data have been standardized using the Observational Medical Outcomes Partnership Common Data Model. 15 In the AoURP, upon consent, participants are asked to complete the Basics survey, in which they may self-report demographic characteristics such as race, ethnicity, and sex at birth.

We filtered the data to include only biallelic, autosomal single-nucleotide variants (SNVs) that had passed AoURP initial quality control. 16 We then removed duplicate-position SNVs and kept only individual genotypes with a genotype quality greater than 20. We further filtered the SNVs based on their Hardy-Weinberg equilibrium P value (>1.0 × 10 −15 ) and missing rate (<5%) across all samples. Next, we divided the samples into 6 groups (Admixed American, African, East Asian, European, Middle Eastern, and South Asian) based on their estimated ancestral populations 16 , 17 and further filtered the SNVs within each population based on minor allele frequency (MAF) (>0.01), missing rate (<0.02), and Hardy-Weinberg equilibrium P value (>1.0 × 10 −6 ). The SNVs were mapped from Genome Reference Consortium Human Build 38 with coordinates to Build 37. Because the existing PRS models have limited transferability across ancestry groups and to ensure appropriate power of the subsequent PRS analysis, we limited our analysis to the populations who had a sample size of greater than 500, resulting in 5964 participants of European ancestry with 5 515 802 common SNVs for analysis.

To generate principal components, we excluded the regions with high linkage disequilibrium, including chr5:44-51.5 megabase (Mb), chr6:25-33.5 Mb, chr8:8-12 Mb, and chr11:45-57 Mb. We then pruned the remaining SNVs using PLINK, version 1.9 (Harvard University), pairwise independence function with 1-kilobase window shifted by 50 base pairs and requiring r 2 < 0.05 between any pair, resulting in 100 983 SNPs for further analysis. 18 Principal component analysis was run using PLINK, version 1.9. The European ancestry linkage disequilibrium reference panel from the 1000 Genomes Project phase 3 was downloaded, and nonambiguous SNPs with MAF greater than 0.01 were kept in the largest European ancestry GWAS summary statistics of BMI. 13 We manually harmonized the strand-flipping SNPs among the SNP information file, GWAS summary statistics files, and the European ancestry PLINK extended map files (.bim).

We used PRS–continuous shrinkage to infer posterior SNP effect sizes under continuous shrinkage priors with a scaling parameter set to 0.01, reflecting the polygenic architecture of BMI. GWAS summary statistics of BMI measured in 681 275 individuals of European ancestry was used to estimate the SNP weights. 19 The scoring command in PLINK, version 1.9, was used to produce the genomewide scores of the AoURP European individuals with their quality-controlled SNP genotype data and these derived SNP weights. 20 Finally, by using the genomewide scores as the dependent variable and the 10 principal components as the independent variable, we performed linear regression, and the obtained residuals were kept for the subsequent analysis. To check the performance of the PRS estimate, we first fit a generalized regression model with obesity status as the dependent variable and the PRS as the independent variable with age, sex, and the top 10 principal components of genetic ancestry as covariates. We then built a subset logistic regression model, which only uses the same set of covariates. By comparing the full model with the subset model, we measured the incremental Nagelkerke R 2 value to quantify how much variance in obesity status was explained by the PRS.

Differences in clinical characteristics across PRS quartiles were assessed using the Wilcoxon rank sum or Kruskal-Wallis test for continuous variables and the Pearson χ 2 test for categorical variables. Cox proportional hazards regression models were used to examine the association among daily step count (considered as a time-varying variable), PRS, and the time to event for obesity, adjusting for age, sex, mean baseline step counts, cancer status, coronary artery disease status, systolic blood pressure, alcohol use, educational level, and interaction term of PRS × mean steps. We presented these results stratified by baseline BMI and provided a model including baseline BMI in eFigure 2 in Supplement 1 as a secondary analysis due to collinearity between BMI and PRS.

Cox proportional hazards regression models were fit on a multiply imputed dataset. Multiple imputation was performed for baseline BMI, alcohol use, educational status, systolic blood pressure, and smoking status using bootstrap and predictive mean matching with the aregImpute function in the Hmisc package of R, version 4.2.2 (R Project for Statistical Computing). Continuous variables were modeled as restricted cubic splines with 3 knots, unless the nonlinear term was not significant, in which case it was modeled as a linear term. Fits and predictions of the Cox proportional hazards regression models were obtained using the rms package in R, version 4.2.2. The Cox proportional hazards regression assumptions were checked using the cox.zph function from the survival package in R, version 4.2.2.

To identify the combinations of PRS and mean daily step counts associated with a hazard ratio (HR) of 1.00, we used a 100-knot spline function to fit the Cox proportional hazards regression ratio model estimations across a range of mean daily step counts for each PRS percentile. We then computed the inverse of the fitted spline function to determine the mean daily step count where the HR equals 1.00 for each PRS percentile. We repeated this process for multiple PRS percentiles to generate a plot of mean daily step counts as a function of PRS percentiles where the HR was 1.00. To estimate the uncertainty around these estimations, we applied a similar spline function to the upper and lower estimated 95% CIs of the Cox proportional hazards regression model to find the 95% CIs for the estimated mean daily step counts at each PRS percentile. Two-sided P < .05 indicated statistical significance.

We identified 3124 participants of European ancestry without obesity at baseline who agreed to link their personal activity data and EHR data and had available genome sequencing. Among those with available data, 2216 of 3051 (73%) were women and 835 of 3051 (27%) were men, and the median age was 52.7 (IQR, 36.4-62.8) years. In terms of race and ethnicity, 2958 participants (95%) were White compared with 141 participants (5%) who were of other race or ethnicity (which may include Asian, Black or African American, Middle Eastern or North African, Native Hawaiian or Other Pacific Islander, multiple races or ethnicities, and unknown race or ethnicity) ( Table ). The analytic sample was restricted to individuals assigned European ancestry based on the All of Us Genomic Research Data Quality Report. 16 A study flowchart detailing the creation of the analytic dataset is provided in eFigure 1 in Supplement 1 . The BMI-based PRS explained 8.3% of the phenotypic variation in obesity (β = 1.76; P  = 2 × 10 −16 ). The median follow-up time was 5.4 (IQR, 3.4-7.0) years and participants walked a median of 8326 (IQR, 6499-10 389) steps/d. The incidence of obesity over the study period was 13% (101 of 781 participants) in the lowest PRS quartile and 43% (335 of 781 participants) in the highest PRS quartile ( P  = 1.0 × 10 −20 ). We observed a decrease in median daily steps when moving from lowest (8599 [IQR, 6751-10 768]) to highest (8115 [IQR, 6340-10 187]) PRS quartile ( P  = .01).

We next modeled obesity risk stratified by PRS percentile with the 50th percentile indexed to an HR for obesity of 1.00 ( Figure 1 ). The association between PRS and incident obesity was direct ( P  = .001) and linear (chunk test for nonlinearity was nonsignificant [ P  = .07]). The PRS and mean daily step count were both independently associated with obesity risk ( Figure 2 ). The 75th percentile BMI PRS demonstrated an 81% increase in obesity risk (HR, 1.81 [95% CI, 1.59-2.05]; P  = 3.57 × 10 −20 ) when compared with the 25th percentile BMI PRS, whereas the 75th percentile median step count demonstrated a 43% reduction in obesity risk (HR, 0.57 [95% CI, 0.49-0.67]; P  = 5.30 × 10 −12 ) when compared with the 25th percentile step count. The PRS × mean steps interaction term was not significant (χ 2 = 1.98; P  = .37).

Individuals with a PRS at the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to reduce the HR for obesity to 1.00 ( Figure 1 ). Conversely, those in the 25th percentile PRS could reach an HR of 1.00 by walking a mean of 3660 (95% CI, 2180-8740) fewer steps than those at the 50th percentile PRS. When assuming a median daily step count of 8740 (cohort median), those in the 75th percentile PRS had an HR for obesity of 1.33 (95% CI, 1.25-1.41), whereas those at the 25th percentile PRS had an obesity HR of 0.74 (95% CI, 0.69-0.79).

The mean daily step count required to achieve an HR for obesity of 1.00 across the full PRS spectrum and stratified by baseline BMI is shown in Figure 3 . To reach an HR of 1.00 for obesity, when stratified by baseline BMI of 22, individuals at the 50th percentile PRS would need to achieve a mean daily step count of 3290 (additional 3460 steps/d); for a baseline BMI of 24, a mean daily step count of 7590 (additional 4430 steps/d); for a baseline BMI of 26, a mean daily step count of 11 890 (additional 5380 steps/d); and for a baseline BMI of 28, a mean daily step count of 16 190 (additional 6350 steps/d).

When adding baseline BMI to the full Cox proportional hazards regression model, daily step count and BMI PRS both remain associated with obesity risk. When comparing individuals at the 75th percentile with those at the 25th percentile, the BMI PRS is associated with a 61% increased risk of obesity (HR, 1.61 [95% CI, 1.45-1.78]). Similarly, when comparing the 75th with the 25th percentiles, daily step count was associated with a 38% lower risk of obesity (HR, 0.62 [95% CI, 0.53-0.72]) (eFigure 2 in Supplement 1 ).

The cumulative incidence of obesity increases over time and with fewer daily steps and higher PRS. The cumulative incidence of obesity would be 2.9% at the 25th percentile, 3.9% at the 50th percentile, and 5.2% at the 75th percentile for PRS in year 1; 10.5% at the 25th percentile, 14.0% at the 50th percentile, and 18.2% at the 75th percentile for PRS in year 3; and 18.5% at the 25th percentile, 24.3% at the 50th percentile, and 30.9% at the 75th percentile for PRS in year 5 ( Figure 4 ). The eTable in Supplement 1 models the expected cumulative incidence of obesity at 1, 3, and 5 years based on PRS and assumed mean daily steps of 7500, 10 000, and 12 500.

We examined the combined association of daily step counts and genetic risk for increased BMI with the incidence of obesity in a large national sample with genome sequencing and long-term activity monitoring data. Lower daily step counts and higher BMI PRS were both independently associated with increased risk of obesity. As the PRS increased, the number of daily steps associated with lower risk of obesity also increased. By combining these data sources, we derived an estimate of the daily step count needed to reduce the risk of obesity based on an individual’s genetic background. Importantly, our findings suggest that genetic risk for obesity is not deterministic but can be overcome by increasing physical activity.

Our findings align with those of prior literature 9 indicating that engaging in physical activity can mitigate genetic obesity risk and highlight the importance of genetic background for individual health and wellness. Using the data from a large population-based sample, Li et al 9 characterized obesity risk by genotyping 12 susceptibility loci and found that higher self-reported physical activity was associated with a 40% reduction in genetic predisposition to obesity. Our study extends these results in 2 important ways. First, we leveraged objectively measured longitudinal activity data from commercial devices to focus on physical activity prior to and leading up to a diagnosis of obesity. Second, we used a more comprehensive genomewide risk assessment in the form of a PRS. Our results indicate that daily step count recommendations to reduce obesity risk may be personalized based on an individual’s genetic background. For instance, individuals with higher genetic risk (ie, 75th percentile PRS) would need to walk a mean of 2280 more steps per day than those at the 50th percentile of genetic risk to have a comparable risk of obesity.

These results suggest that population-based recommendations that do not account for genetic background may not accurately represent the amount of physical activity needed to reduce the risk of obesity. Population-based exercise recommendations may overestimate or underestimate physical activity needs, depending on one’s genetic background. Underestimation of physical activity required to reduce obesity risk has the potential to be particularly detrimental to public health efforts to reduce weight-related morbidity. As such, integration of activity and genetic data could facilitate personalized activity recommendations that account for an individual’s genetic profile. The widespread use of wearable devices and the increasing demand for genetic information from both clinical and direct-to-consumer sources may soon permit testing the value of personalized activity recommendations. Efforts to integrate wearable devices and genomic data into the EHR further support the potential future clinical utility of merging these data sources to personalize lifestyle recommendations. Thus, our findings support the need for a prospective trial investigating the impact of tailoring step counts by genetic risk on chronic disease outcomes.

The most important limitation of this work is the lack of diversity and inclusion only of individuals with European ancestry. These findings will need validation in a more diverse population. Our cohort only included individuals who already owned a fitness tracking device and agreed to link their activity data to the AoURP dataset, which may not be generalizable to other populations. We cannot account for unmeasured confounding, and the potential for reverse causation still exists. We attempted to diminish the latter concern by excluding prevalent obesity and incident cases within the first 6 months of monitoring. Genetic risk was simplified to be specific to increased BMI; however, genetic risk for other cardiometabolic conditions could also inform obesity risk. Nongenetic factors that contribute to obesity risk such as dietary patterns were not available, reducing the explanatory power of the model. It is unlikely that the widespread use of drug classes targeting weight loss affects the generalizability of our results, because such drugs are rarely prescribed for obesity prevention, and our study focused on individuals who were not obese at baseline. Indeed, less than 0.5% of our cohort was exposed to a medication class targeting weight loss (phentermine, orlistat, or glucagonlike peptide-1 receptor agonists) prior to incident obesity or censoring. Finally, some fitness activity tracking devices may not capture nonambulatory activity as well as triaxial accelerometers.

This cohort study used longitudinal activity data from commercial wearable devices, genome sequencing, and clinical data to support the notion that higher daily step counts can mitigate genetic risk for obesity. These results have important clinical and public health implications and may offer a novel strategy for addressing the obesity epidemic by informing activity recommendations that incorporate genetic information.

Accepted for Publication: January 30, 2024.

Published: March 27, 2024. doi:10.1001/jamanetworkopen.2024.3821

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Brittain EL et al. JAMA Network Open .

Corresponding Author: Evan L. Brittain, MD, MSc ( [email protected] ) and Douglas M. Ruderfer, PhD ( [email protected] ), Vanderbilt University Medical Center, 2525 West End Ave, Suite 300A, Nashville, TN 37203.

Author Contributions: Drs Brittain and Ruderfer had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Brittain, Annis, Master, Roden, Ruderfer.

Acquisition, analysis, or interpretation of data: Brittain, Han, Annis, Master, Hughes, Harris, Ruderfer.

Drafting of the manuscript: Brittain, Han, Annis, Master, Ruderfer.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Brittain, Han, Annis, Master.

Obtained funding: Brittain, Harris.

Administrative, technical, or material support: Brittain, Annis, Master, Roden.

Supervision: Brittain, Ruderfer.

Conflict of Interest Disclosures: Dr Brittain reported receiving a gift from Google LLC during the conduct of the study. Dr Ruderfer reported serving on the advisory board of Illumina Inc and Alkermes PLC and receiving grant funding from PTC Therapeutics outside the submitted work. No other disclosures were reported.

Funding/Support: The All of Us Research Program is supported by grants 1 OT2 OD026549, 1 OT2 OD026554, 1 OT2 OD026557, 1 OT2 OD026556, 1 OT2 OD026550, 1 OT2 OD 026552, 1 OT2 OD026553, 1 OT2 OD026548, 1 OT2 OD026551, 1 OT2 OD026555, IAA AOD21037, AOD22003, AOD16037, and AOD21041 (regional medical centers); grant HHSN 263201600085U (federally qualified health centers); grant U2C OD023196 (data and research center); 1 U24 OD023121 (Biobank); U24 OD023176 (participant center); U24 OD023163 (participant technology systems center); grants 3 OT2 OD023205 and 3 OT2 OD023206 (communications and engagement); and grants 1 OT2 OD025277, 3 OT2 OD025315, 1 OT2 OD025337, and 1 OT2 OD025276 (community partners) from the National Institutes of Health (NIH). This study is also supported by grants R01 HL146588 (Dr Brittain), R61 HL158941 (Dr Brittain), and R21 HL172038 (Drs Brittain and Ruderfer) from the NIH.

Role of the Funder/Sponsor: The NIH had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: The All of Us Research Program would not be possible without the partnership of its participants.

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Sports Nutrition: Diets, Selection Factors, Recommendations

Kristina a. malsagova.

1 Biobanking Group, Branch of IBMC “Scientific and Education Center” Bolshoy Nikolovorobinsky Lane, 109028 Moscow, Russia; [email protected] (A.T.K.); moc.liamg@aylivna (A.A.S.); [email protected] (A.A.S.); [email protected] (A.A.I.); [email protected] (T.V.B.); moc.liamg@1avehsyak (A.L.K.)

Arthur T. Kopylov

Alexandra a. sinitsyna, alexander a. stepanov, alexander a. izotov, tatyana v. butkova, konstantin chingin.

2 Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China; [email protected]

Mikhail S. Klyuchnikov

3 State Research Center Burnasyan of the Federal Medical Biophysical Centre of the Federal Medical Biological Agency of Russia, 123098 Moscow, Russia; moc.em@vokinhcujlk

Anna L. Kaysheva

Associated data.

This is a review paper that collected from public data listed in the “Reference” and from open access web-source Pubmed.

An athlete’s diet is influenced by external and internal factors that can reduce or exacerbate exercise-induced food intolerance/allergy symptoms. This review highlights many factors that influence food choices. However, it is important to remember that these food choices are dynamic, and their effectiveness varies with the time, location, and environmental factors in which the athlete chooses the food. Therefore, before training and competition, athletes should follow the recommendations of physicians and nutritionists. It is important to study and understand the nutritional strategies and trends that athletes use before and during training or competitions. This will identify future clinical trials that can be conducted to identify specific foods that athletes can consume to minimize negative symptoms associated with their consumption and optimize training outcomes.

1. Introduction

Nutrition is considered one of the foundations of athletic performance, and post-workout nutritional recommendations are fundamental to the effectiveness of recovery and adaptive processes. Therefore, an effective recovery strategy between workouts or during competition can maximize adaptive responses to various mechanisms of fatigue, improving muscle function and increasing exercise tolerance. An effective intervention to restore the physical fitness of an athlete by monitoring the regimen and diet, timely admission, and the specified quality and quantity of food components is considered fundamental [ 1 ].

Currently, new directions in dietetics are being formed, focusing on the creation of personalized diets. These include (1) genetic studies that are likely to determine people’s predisposition to a particular type of food and the degree of risk of food-related diseases [ 2 ]; (2) studies on the diversity of the human microbiota, the characteristics of digestion, and the state of the intestinal barrier [ 3 , 4 ]; and (3) studies of individual responses of the immune system to food antigens that cause changes in food tolerance and reactivity of the adaptive immune response. The adaptive immune response is provided by lymphocyte functions (acquired immunity) and plays an important role in the defense from infection and elimination of exogenous pathogens in vivo [ 5 , 6 , 7 , 8 ].

Food allergy is defined as an adverse immune-mediated reaction that occurs when exposed to a food agent and disappears when it is withdrawn [ 9 ]. Other non-allergic food reactions are intolerant and do not affect the immune system [ 10 ]. Adverse food reactions can also occur due to toxins, manifestations of congenital metabolic disorders [ 10 ], and functional disorders of the gastrointestinal tract. Food allergy is a health problem affecting 3% to 10% of the worldwide population of adults and up to 8% of children [ 11 ]; approximately 2% to 20% of the world’s population has a food intolerance [ 12 ].

In addition, food intolerance is on the rise among athletes, but the use of unverified food intolerance tests calls into question an accurate assessment of the state of true intolerance in the population [ 12 ]. While physical activity is good for people’s health, intense training, as in the case of elite athletes, harms the immune system and increases the permeability of the gastrointestinal tract. Some studies have linked food intolerance in elite athletes to excessive physical activity [ 12 ]. Therefore, in the research [ 12 ], an experimental longitudinal study lasting three months was conducted to assess the impact of food intolerance on sports performance and the health of elite athletes. According to the results of a food intolerance test, an individual elimination diet was drawn up. The blood test showed a decrease in the level of food intolerance after the diet in each athlete, which indicated that the elimination diet significantly improved the athlete’s well-being, making it possible to achieve a faster decrease in heart rate after cardiopulmonary testing.

The primary manifestation of food intolerance is malabsorption of lactose and fructose, resulting from an insufficient supply of enzymes and insufficient functionality of transporters [ 10 , 13 , 14 ]. Symptoms can vary, including gastrointestinal upsets (bloating, loose stools, abdominal pain) and/or extraintestinal symptoms (fatigue, headaches, and cognitive problems) that appear hours or days after eating [ 10 ]. Some of these symptoms overlap with symptoms of irritable bowel syndrome and exercise-induced functional gastrointestinal disturbances [ 10 , 15 ]. Given the ambiguous nature of food intolerance, its diagnosis, as a rule, is performed independently by athletes with the subsequent cancelation of certain food products or a group of products [ 9 , 16 ].

Gluten-free diets are under active development, and there is evidence of the benefits of a diet low in fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) for reducing exercise-induced gastrointestinal symptoms [ 9 ].

The review purposed to assess the current state of the eating behavior of athletes, food market development, food choice rationality, and effectiveness of the developed and elaborated recommendations. The primary analysis was performed using a text-mining tool to highlight and pick up concepts from the PubMed ScanBious source ( , accessed on 15 September 2021) [ 17 , 18 ]. The combined pool of articles of interest was comprised of 94 studies within 10 years depth. Additionally, we analyzed the literature from the past ten years and used secondary literature sources. The search was conducted using such resources as the National Library of Medicine (PubMed) and Mendeley for the keywords (MeSH) “sports”, “athletes”, “diet”, “nutritional requirements”, “physical endurance”.

2. Factors Influencing Diet Choices of Athletes

Many factors are known to influence food choices, including personal taste, affordability, cost, sustainability, culture, family, and religious beliefs ( Figure 1 ) [ 19 , 20 , 21 ]. In addition to these factors, individual knowledge of food and nutritional science also influences choices [ 22 ].

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Object name is nutrients-13-03771-g001.jpg

Factors influencing dietary choices of athletes.

Among athletes, nutrition plays an important role since the regimen and composition of the diet are associated with success in sports [ 23 , 24 ]. Concerns about weight and body shape strongly influence food choices for the general population [ 12 ] and have a similar effect on athletes, where attempts to achieve their goals are associated with external data on physique, weight, and performance [ 25 ]. Factors affecting food choices can differ depending on an athletes priorities, as sports participants can range from recreational (leisure or recreational sports) to elite (national or international competition) [ 26 , 27 ].

2.1. Physiobiological Factors

Historically, the main factor influencing individual food choices has been satisfying hunger, usually driven by appetite and fullness [ 28 ]. Temporary suppression of appetite after moderate or vigorous exercise may be due to changes in appetite-regulating hormones, body temperature, and/or decreased blood flow in the intestines [ 29 , 30 , 31 ]. In addition, appetite is suppressed at high altitudes and during exercise in hot environments [ 31 ]. In addition, research has shown that exercise at lower temperatures can stimulate appetite based on increased energy intake [ 32 ], and that athletes can eat despite a loss of appetite [ 33 ], or ignore hunger cues and limit their food intake to achieve weight targets [ 34 ]. This behavior suggests that hunger may not be the main motivator for food choices. Relying on hunger as an indicator of an athlete’s energy needs may be inappropriate when working with this population [ 35 ].

The hunger and satiety feeling are influenced by the amount of consumed food and its chemical and physical properties [ 36 , 37 , 38 ]. Being a key parameter that controls nutrient intake and affects the body weight, satiety is comprehensively controlled and depends on food ingredients [ 37 ]. Many athletes need strict weight control to achieve their goals in the competition season [ 36 ]. Controlled consumption of fiber (including oatmeal and barley), dietary fat, and carbohydrates is the main strategy to determine a satiety diet [ 37 , 38 ].

Homeostatic mechanisms related to the balance of fats, carbohydrates, and proteins are thought to help regulate eating behavior and energy balance [ 29 , 39 ]. Increased energy and macronutrient intake after exercise may be related to substrate oxidation, so athletes are more likely to consume foods high in carbohydrates, post-workout, to restore carbohydrate balance [ 40 ]. However, this is not always observed in scientific research, as there are differences potentially associated with the design of the experiment and the population being studied [ 40 , 41 ]. Much of the research on macronutrient regulatory systems relates to energy intake and obesity [ 39 , 41 , 42 ]. Much of the research on macronutrient regulatory systems relates to energy intake and obesity. The results may apply differently to populations of athletes wherein carbohydrate intake during exercise is common practice and wherein training adaptations may affect product use [ 43 ].

Taste is an important determinant of food choices because the aroma, taste, and appearance of foods are pleasurable, activating a rich and varied sensory experience [ 44 , 45 ]. However, among elite athletes, the taste may become a less critical factor before an important game or event when preference is given to products that improve athletic performance [ 26 , 46 ]. For example, some athletes avoid preferred foods before a competition to achieve weight-related goals [ 34 ]. The importance of food taste can differ by gender, income, and age and is often viewed concerning other priorities such as health, weight, or financial concerns [ 19 , 29 , 47 ].

Athletes with food allergies or intolerances tend to avoid certain foods to reduce the risk of an allergic reaction, or to minimize the development of reactions associated with, for example, gastrointestinal disorders (heartburn, bloating, diarrhea, cramps, nausea, and vomiting) during exercise [ 29 , 48 , 49 ]. Gastrointestinal problems impair performance or subsequent recovery and up to 30%-50% of athletes (mostly endurance athletes) face such complaints [ 50 ] Following intense exercise, especially with hypohydration, the decrease of mesenteric blood flow is considered the main symptom of the development of gastrointestinal issues. Since the severity of gastrointestinal upset affects performance and overall competitive results, post-exercise mesenteric blood flow holds a key position regarding the food choice as much before as during the competition. Nutrition should ensure rapid gastric emptying and absorption of water and nutrients, as well as maintaining adequate internal vascular perfusion. It has been shown, that athletes frequently change their diet and food preferences before a competition to avoid gastrointestinal discomfort [ 33 , 51 ].

2.2. Lifestyle Factors

Important factors regarding food choices vary according to lifestyle preferences [ 52 , 53 ]. People may choose to play sports to become physically active. Motivation for this can be to maintain or improve health, the desire to have a lean body, and optimal weight [ 54 ]. Several studies have shown that performance is one of the most important factors affecting food choice for athletes, both for individual and team sports [ 23 , 33 , 55 ]. In addition, an athlete’s attention regarding choice of nutrition may vary depending on the phase of the season, the type of sport, the fitness of the athlete, and the level of competition [ 33 , 46 , 55 ]. For example, when training performance is not particularly critical, hockey players in the off-season are more relaxed about food choices, while more competitive triathletes tend to prefer food that maximizes performance. Strength athletes place less emphasis on performance factors (e.g., nutrient content in foods) than endurance athletes [ 55 ]. It is important to keep these points in mind when working with athletes.

Nutritional awareness and bias can also influence food choices [ 56 ]. Thus, an athlete’s knowledge of foods, dietary patterns, and their role in health and athletic performance can influence their dietary choices. However, despite awareness in the field of sports nutrition, athletes do not always apply the knowledge gained in practice [ 57 ]. Athletes at a higher level (international or national) have higher nutrition knowledge and are more responsible in their food choices while prioritizing performance [ 58 , 59 ]. Although limited research suggests that nutritional knowledge can influence the diet of athletes, further research is needed that considers additional factors that may be important in an athlete’s diet.

2.3. Psychological Factors

Weight is an important factor in food choice [ 60 ]. Cognitive or conscious dietary restriction to control body weight may be characteristic of athletes trying to change body weight to improve athletic performance [ 33 ], or gain athletic form [ 24 , 61 ]. Therefore, athletes are at an increased risk of eating disorders in sports where more attention is paid to body weight and shape (gymnastics, swimming) [ 25 , 62 ]. Consequently, athletes can restrict food intake to achieve the “ideal” weight for esthetic or performance reasons. Overall, weight problems can be a driving force in the dietary choices of many athletes, but more research is needed in this area.

Some studies have shown that people eat more than just to satisfy hunger [ 20 , 28 , 58 ]. Opportunities to consume a variety of delicious, readily available, and, for the most part, inexpensive foods continue to grow. For this reason, many argue that, currently, food choice is primarily influenced by the so-called hedonic hunger when people tend to eat for pleasure in the absence of an energy deficit [ 28 ]. In [ 63 ], subjects with compensatory energy intake compensated for energy expended on exercise by increasing the amount of food they eat, while subjects with non-compensatory energy intake did not.

2.4. Social Factors

Diet composition can also be determined by the social factors associated with daily life [ 64 ]. For example, one’s schedule of work, school, training, competition, or other amusement can determine food choice, while preference is given to food that can be quickly and easily prepared [ 23 , 65 , 66 ]. It is also important for athletes to meet their energy needs after exercise, so they may have frequent consumption of food that is convenient and easy to prepare [ 33 , 67 , 68 ]. Some athletes report overeating in dining rooms due to the abundance of options available and/or repeated trips to the grocery line after observing teammates eating [ 23 ]. Similarly, the dietary choices of younger athletes can be influenced by the dietary choices of older and more experienced teammates [ 23 ]. Food marketing, media, and advertising are common sources of nutritional information for many consumers, including athletes, and this can influence their food choices [ 69 , 70 ].

Thus, research shows that dietary accessibility, social support, habits, and marketing can influence food choices. However, it is unclear how important these factors are for athletes, and further research in this area is needed.

Athletes have different religious and cultural backgrounds associated with certain customs, traditions, values, and beliefs, which are usually passed down from generation to generation and can influence their choice of food [ 71 , 72 ]. For some athletes, family traditions and ethnic background do not matter much when choosing food, while for others, food choices based on religious beliefs are paramount [ 73 ]. Indeed, long-standing customs may prevail over health and sport-recommendations recommendations in favor of the performance seen in heavy sports such as wrestling and horse racing [ 34 , 74 ]. In general, cultural factors are important determinants of food choices and can be important for athletes.

2.5. Economic Factors

Choice of food products is often determined by cost. This factor is especially important for people with low incomes and students [ 66 ]. For athletes, the choice of a healthy diet is often limited by their financial situation [ 69 , 75 ]. Participation in certain sports can be costly and therefore only attract those who can afford it [ 26 ]. Sometimes, one’s level of income is not always the decisive factor in food choice. For many, it is important to obtain good value for money [ 76 ].

The most common are gluten-free (GF), vegetarian, and lean diets. These diets are popular diets for the entire population, however, they are also used by some professional athletes to maintain health. An increasingly popular diet low in FODMAPs is used to reduce exercise-related gastrointestinal symptoms [ 15 ]. However, the potential consequences of dietary restrictions and special diets should be carefully evaluated [ 77 ].

3.1. Gluten-Free Diet

Over the past ten years, the market for GF products has grown by 110%. Consumption of GF foods is relevant for people with celiac disease (CD), gluten intolerance (GI), and wheat allergy (WA). However, it is an autoimmune disease that interferes with intestinal absorption due to inflammation and atrophy of the villi [ 78 ]. CD prevalence is estimated to be approximately 1% [ 79 ].

Despite the different etiology and severity of manifestation, the symptoms of celiac disease (CD) and gluten intolerance (GI) are very similar - diarrhea, bloating and gas, abdominal pain, nausea and constipation, headache and fatigue, etc.

Despite different etiology and severity of manifestation, symptoms of celiac disease (CD) and gluten intolerance (GI) are quite similar and include diarrhea, bloating and gas, abdominal pain, nausea and constipation, headache and fatigue, etc. However, the diagnosis of GI is difficult because physicians are less aware of gluten intolerance than gluten disease or wheat allergy. Thus, GI is generally established after excluding celiac disease and wheat allergy [ 80 ].

Some may eat small amounts of gluten until they reach a threshold, while others are gluten-intolerant. WA differs from GI and CD. People with WA undergo a systemic reaction to gluten. The symptoms of WA are similar to those of other allergies, such as hives and swelling. However, for CD, GI, and WA, therapy aims to eliminate gluten from the diet.

Strict adherence to a gluten-free diet (GFD) excludes all sources of gluten (a storage protein component containing glutenin and gliadin) because eating foods containing gluten or gliadin (wheat, barley, and rye) is accompanied by an inappropriate immune response [ 78 ]. Gliadin is not fully digested or cleared from the body, and does not induce an immune response in people without CD. A previous study [ 79 ] provided information on the types of foods and ingredients relevant to the GFD, as well as foods rich in gluten or containing hidden gluten.

GFD commitment has become popular among athletes. GFD is known to be essential for maintaining health and controlling symptoms in people with gluten sensitivities, but as a result of its marketing strategy, a GFD is in a “privileged” position with the promise of overall health and ergogenic benefits [ 16 ]. The main reason for adherence to a GFD in athletes is the widespread belief that gluten causes gastrointestinal pathology and inflammation. The number of athletes adhering to a GFD is four times higher than that of the part of the general population estimated to require gluten restriction or elimination [ 81 ]. According to Lis et al., 41% of athletes without CD report adherence to a GFD, while about 60% self-identified GI [ 16 ]. A study [ 78 ] investigated the effect of a GFD in athletes without CD on endurance. The findings showed that a seven-day GFD did not positively or negatively affect gastrointestinal health, inflammation, or the overall well-being and performance of non-celiac cycling athletes. However, it is important to consider a higher likelihood of exercise-induced gastrointestinal syndromes [ 15 ].

In addition, the elimination of gluten from the diet means that many carbohydrate foods consumed by endurance athletes are also eliminated from the diet [ 82 ]. Iron deficiency anemia occurs in 70% of people with CD [ 83 ]. Therefore, it is necessary for such athletes to carefully plan their nutritional needs for training and competition [ 84 ]. In cases where CD is accompanied by iron-deficiency anemia, it is vital to follow an iron-rich GFD. A study [ 82 ] analyzed nutritional intake during training and competition in the 384 km K4 cycling race of an aspiring long-distance cyclist diagnosed with CD. During the competition, the athlete reported nausea when they tried to consume sugary drinks or marmalade, so their desire to eat decreased. This was probably due to a combination of prolonged consumption of sugary foods and fatigue. Furthermore, the use of dry and crumbly forms of GF foods also proved to be problematic, as some of the food was lost, and the consumption of dry foods can increase the urge to drink. In addition, GF foods tend to be high in calories, which can slow stomach emptying and cause discomfort during exercise [ 85 ]. GF foods are energetically rich, but low protein content makes athletes feel hungry despite meals. As a result, against the background of hunger, the development of psychological disorders is possible. The athlete completed his main task to finish the race, but the total race time was almost 2 h slower than expected. This could have been due to insufficient energy intake, which led to the early onset of fatigue. Therefore, for athletes with CD during training and competition, it is necessary to consider alternative dietary regimens to increase endurance [ 82 ].

3.2. FODMAPs Diet

FODMAP is a family of fermentable short-chain carbohydrates found in a wide variety of foods and components [ 9 , 86 ]. The FODMAP diet has become an advanced treatment for irritable bowel syndrome symptoms with a 70% success rate [ 87 ]. Some components of FODMAPs are poorly digested, but gastrointestinal symptoms are often absent or only mild. Athletes performing strenuous exercise often experience impaired function concerning the integrity of the gastrointestinal tract. At the same time, undigested food molecules increase the osmotic load in the small intestine, the osmotic translocation of water and weight loss, and the development of diarrhea or constipation. The consumption of carbohydrates is necessary to maintain energy requirements [ 49 ].

Athlete-specific data support the concept that FODMAPs affect exercise-associated gastrointestinal symptoms [ 88 , 89 ]. Gastrointestinal symptoms can occur after intense exercise, which can affect energy replenishment. This is especially important when competitions take place over several days or several times a day. Often athletes exclude foods high in FODMAPs such as lactose, fructose with excess glucose, galactooligosaccharides, polyols, and fructans) on their own [ 90 ]. Some studies have highlighted the effectiveness of using a low FODMAP diet to reduce the severity of gastrointestinal symptoms during and outside of exercise [ 89 , 91 ].

Therefore, in the study [ 90 ], 910 athletes were interviewed to assess their attitude toward the exclusion of food/ingredients associated with gastrointestinal disorders. After eliminating a large number of FODMAP-containing foods, athletes reported an improvement in symptoms ranging from 68.2% (polyols) to 83.7% (lactose). More often, athletes excluded lactose sources and, to a lesser extent, other high FODMAP foods. Lactose elimination can be achieved by eliminating all sources of lactose, limiting exclusively concentrated sources, or eliminating only pre-workout. However, the elimination of lactose by athletes to reduce gastrointestinal symptoms can lead to calcium deficiency, so individual dietary strategies should be followed to ensure adequate intake [ 92 ].

3.3. Plant-Based Diets

According to a study [ 93 ], there is a growing interest in plant-based diets, especially in relation to vegan diets and semi-vegetarian or flexitarian diets among athletes. Approximately 8% of international athletes follow a vegetarian diet, and 1% are vegans [ 94 ].

Vegetarian and vegan diets have been linked to a reduced risk of chronic diseases among non-athletes [ 94 ]. In their work, Craddock et al. performed a comparative analysis of physical performance in athletes, which did not reveal clear differences between a vegetarian diet and an omnivorous mixed diet. The prevailing vegetarian diet did not improve or decrease the performance of the athletes [ 95 ]. However, owing to its high carbohydrate content, a vegetarian diet can be beneficial for energy storage. In addition, antioxidants and phytochemicals are helpful [ 95 , 96 ]. However, plant-based diets can reduce certain nutrients in the body, including omega-3 fatty acids, iron, zinc, calcium, vitamin D, iodine, and vitamin B12. These nutrients are less present in plant foods or are less readily absorbed from plants than from animal sources [ 96 ].

In general, plant-based diets containing various whole grains, vegetables, fruits, legumes, nuts, and seeds can provide proteins, carbohydrates, fats, vitamins, and minerals. Depending on your dietary choices, focusing on foods high in protein, iron, zinc, calcium, and vitamin B12 (such as yeast extract foods) will ensure adequate nutritional status. While research strongly suggests that a plant-based diet may provide some health benefits, there is little evidence that vegetarian diets are better than that of omnivores in terms of improving fitness, health, and performance.

In their study, Pelly et al. studied the diet of athletes participating in major international competitions during the 2010 Commonwealth Games in Delhi. In total, 351 athletes were questioned. Most athletes (62%) reported following one or more dietary regimens, with 50% following a nutritional-based diet. Athletes from weight classes and esthetic (28%) and strength/sprint (41%) sports followed low-fat and high-protein regimens, respectively. Other specialized diets were followed by 33% of the participants, with the most frequently reported avoiding red meat (13%), vegetarian diets (7%), halal (6%), and low lactose (5%) diets. More athletes from non-Western regions followed a vegetarian diet, while more vegetarians reported avoiding supplements and wheat [ 97 ].

Therefore, special diets are effective for some athletes. However, each of them should be carefully evaluated, along with the rationale for choosing the diet. To optimize nutrition for high athletic performance, one should consult with an accredited dietitian as well as medical and sport sciences personnel. Organizers of major sporting events must ensure the availability of adequate nutrition and food supplies.

4. Functional Food for Athletes

Sports nutrition guidelines indicate that it is necessary to use a large quantity of carbohydrates during training for athletes in sports related activity for endurance. Most commercially available energy drinks, smoothies, and bars have a high glycemic index. However, high carbohydrate intake can cause gastrointestinal upset because of its high osmolality (see the FODMAP diet) [ 98 ]. For people with glucose intolerance, diabetes, or hyperglycemia, during exercise, such prescriptions can be dangerous or even fatal [ 1 , 99 , 100 , 101 , 102 ].

Grubic et al. developed a glucose-free food bar that meets sports nutrition guidelines. Ingestion of a bar containing whey protein (20 g), isomaltooligosaccharides of plant fibers (25 g), and fats (7 g) is effective in glucose homeostasis and performance, compared to the experience of conventional carbohydrate intake. Subjects were asked to take a food bar 30 min before, during, and after exercise during the study. The training program consisted of 11 resistance exercises (three sets of ten repetitions), followed by agility exercises and timed sprints. This study showed that the glycemic and insulinemic responses were more favorable for the maintenance of euglycemia than the intake of an equivalent amount of carbohydrates (dextrose) [ 103 ], which in turn allowed maintenance of the necessary level of performance during training and reduced muscle pain after exercise.

Replacing carbohydrates rapidly is an urgent problem for athletes, and today, solutions are available. Cereal foods, such as rice, can effectively maintain energy levels. More recently, Ishihara et al. modified a rice cake by the addition of sweet potatoes and evaluated the availability of raw rice as a source of carbohydrates during endurance training [ 104 ]. The training protocol consisted of one hour of continuous race time. Evaluation using a visual analog scale showed that this product significantly suppressed the degree of hunger ( p < 0.05) and, more significantly, tended to decrease thirst ( p < 0.10) during the training period.

Dairy products are also in demand, as they are some of the best muscle-building aids in sports [ 105 , 106 , 107 ]. However, athletes often experience lactose intolerance. In this case, milk must be replaced with products containing enzymes, such as fermented milk. The digestibility of such products reaches 91%, in contrast to the digestibility of milk, which is 34% [ 108 ].

Russian scientists reported that a specialized food product for athletes was developed based on fermented milk whey “MDX” (LLC “PROBIO,” RF) to increase adaptive capabilities [ 109 ]. The test drink, obtained by microbiological processing of whey (cheese, curd, and casein), using industrial cultures of lactic acid microorganisms and subsequent low-temperature concentration, contained a formula of: hydrolyzed whey protein, oligopeptides, and free amino acids, glucose, galactose, lactic acid, acid, C, E, B1, B2, B6, PP, β-carotene, folic acid, as well as endosomal enzymes of lactic acid bacteria; microelements, Cu 2+ , Zn 2+ , Mn 2+ , Fe 2+ , and macroelements, K + , Na + , Ca 2+ , Mg 2+ and phosphorus. The product also contained a live culture of lactic acid bacteria: Lactococcus lactis , L. thermohilus , and L. bulgaricus (1.2 × 108 CFU/cm 3 ). The study involved 30 cross-country skiers (average age 19.5 ± 1.8 years). Twelve skiers in the main group consumed the specialized food product for 21 days, and 18 skiers took a placebo. The revealed functional changes were most likely associated with an absolute increase (by 31%, p < 0.05) in relative physical performance (by 33%, p < 0.05) and in the aerobic endurance of the skiers.

Currently, there is a hypothesis about the need for a carbohydrate-protein mixture (CHO:PRO) in the diet of sprint athletes [ 1 , 110 ]. Some studies have shown that CHO:PRO in the diet increases muscle glycogen stores, decreases muscle damage, and improves exercise adaptation [ 1 ]. The carbohydrate-protein blend improves the rapid recovery process by stimulating muscle protein synthesis, as well as activating both the target signaling mechanism of rapamycin [ 111 ] and more efficient storage of glycogen through an insulinotropic response [ 112 ].

CHO increases the amount of insulin, thereby attenuating the post-workout cortisol response. Combined with the anabolic response to protein supplementation, this has a positive effect on protein synthesis. In addition, it has been shown that weakening of the cortisol response is greatest with the combined use of CHO and PRO versus taking only CHO or PRO in a sample of untrained young adult men [ 113 ].

da Silva et al. developed a skimmed, lactose-free, and leucine-fortified cow milk chocolate (CML) prototype. The developers proposed a lactose-free “ready-to-eat” product that was tested on a group of soccer players. The findings suggest that CML tasted good and was well tolerated by athletes in this study [ 114 ]. This suggested that CML could be an alternative sports drink that would provide post-workout energy recovery while avoiding discomfort for athletes with lactose intolerance.

Born et al. conducted a comparative analysis of the two commercial products. Chocolate Milk (CM) (Horizon Organic Low-Fat Chocolate Milk, WhiteWave Foods Company, Denver, CO, USA) used a mixture of carbohydrates and proteins, CHO: PRO, as an additive. A commercially available sports drink was used as a CHO additive. Research into the effects of beverage-based supplements on the recovery of adolescent athletes has been performed in the field. The analysis showed a decrease in bench press strength after five weeks of training in the CHO group compared to an increase in strength in the CM group [ 115 ].

Athletes and athlete support specialists may be interested in special formulations as an alternative to regular sports drinks designed to meet the high metabolic costs of grueling team sports. Such products are of interest as an opportunity to prevent gastrointestinal disorders. These studies prove that the intake of alternative products is rational for addressing food intolerance and systematic training loads and effective for increasing the adaptive capabilities of athletes.

5. Personalized Nutrition for Athletes

The introduction of omics technologies into professional sport practice provides an opportunity for a personalized (personified) approach for various areas, including nutrition.

Recently, concepts such as nutrigenomics and nutrigenetics have begun to be employed in sports genetics. Nutrigenomics describes the effect of food components on gene expression, whereas nutrigenetics intends to determine the optimal diet for a particular person depending on personal genetic status and relevant response to food. It is also important to take into account that each person responds differently depending on their genotypic and phenotypic characteristics even if nutrients act in a dose-dependent manner, modulating some physiological functions [ 116 ]. In particular, the cross-talk between genes and nutrients can affect the amount and type of nutrients consumed with food, and therefore the functions of the body [ 117 ].

The amount and the type of protein and carbohydrate in a -personalized diet are critical to muscle growth and overall performance. Over the past years, there is significant progress in the understanding of the mechanism regulating gene expression and protein synthesis events, in the evaluation of genetic variations, and in how to figure out essential nutrients capable for activating such processes.

Genetic variations can influence the total amount of bioactive peptides obtained from the protein source and, hence, their accessibility to muscle growth. Different foods are ambiguous in protein quality as an instant source of limiting amino acids. Leucine, for example, is a key factor of protein synthesis and enhances the activity of various kinases that regulate the onset of translation processes such as the mTOR signaling pathway. The excessive functionality of the mTOR pathway, caused by genetic polymorphisms, affects muscle growth and performance in athletes by means of nutrient absorption and protein synthesis. Considering these genetic data, it is required proper nutritional strategies that balance the intake of carbohydrates and protein from food and supplements.

Genetic polymorphisms in LAT1 and LAT2 genes (encoding BCAA amino acid transporters) may impact the rate of leucine post-ingestion absorption, thence, reducing the amount of leucine available for protein synthesis [ 118 ].

The past decade is highlighted by rigorous studying of genetic polymorphisms and environmental factors both affecting lipids transport and plasma lipids level. This knowledge is essential to render a new personalized strategy of a balanced diet for athletes. The effect of minor rs4315495 SNP in LPIN1 and the diet on serological lipids profile was examined [ 119 ]. Participants, carrying such SNP and maintaining a high-protein diet, demonstrated diminished circulating triacylglycerides level.

Also, due care should be taken for the daily amount of minerals and vitamins in order to find the proper personal dose of micronutrients. In particular, new nutrigenomic studies highlight the importance of proper daily intake of certain minerals and vitamins to maximize athlete performance and proper recovery from exercise [ 119 ].

Nevertheless, despite the growing market of genetic testing aimed to predict athlete performance and talent, nutrigenetic and nutrigenomic testing are less known and less utilized. The most critical challenge is the complexity in the estimation of functional roles of various polymorphisms, specifically because any polymorphism can directly or indirectly act on other genes, proteins, or metabolic pathways. Hence, more research is needed to establish the complex network of gene and nutrient associations capable of determining the type of essential nutrients to be integrated and the type of nutrients with harmful potency.

6. Nutritional Advisory Services and Recommendations

In a major international competition, the Taipei Universiade (2017), a nutrition service was launched by a nutritionist, using FoodWorks (Nutrition Analysis Software, to provide nutritional advice for improving the diet of young and adult athletes.

The results of this event showed that the consumers of the service were interested in food allergy/intolerance issues. Most athletes seeking nutritional advice had no previous nutritional support (86.5%) and wanted nutritional plans and performance-related advice (81.1%).

At the 2010 Commonwealth Games in Delhi, a study was conducted that aimed to (1) determine the qualifications of nutritionists who may be required at points of sale of food organized at major competitions, (2) examine the opinions of athletes regarding the use of nutrition support services, and (3) analyze the relationship of their sport with the existing knowledge about nutrition [ 120 ]. Inquiries were received from athletes from the Western Regions regarding nutrition and special/therapeutic dietary requirements (mainly regarding food allergies and intolerances). Athletes from non-Western regions and athletes in weight categories made more requests for sports nutrition and consulted more often.

Currently, a large selection of test methods can be used to determine the prevalence of intolerance of certain foods and/or their components. The results of these analyses, as a rule, were supplemented by the recommendations of a specialist. Table 1 provides a list of laboratory products designed to analyze food intolerance or allergies.

List of commercial products for detecting food intolerances or allergies.

Furthermore, digestion control applications are currently being developed. For example, FoodMarble ( , accessed on 15 September 2021) developed the FoodMarble AIRE, a portable breath monitor with connected app. The FoodMarble AIRE allows the analysis of the digestion process in real-time.

In addition to the above commercial products, recommendations for athletes are being developed by the international nutrition community, the Ministry of Sports, and researchers( Table 2 ).

Recommendations on the peculiarities of the nutritional diet by sports scientific and medical organizations and scientific research.

Evaluating athlete nutrition is challenging due to the influence of periodic exercise and other sport-specific factors such as frequent overeating, large portion sizes, and widespread use of sports nutrition and supplements [ 67 , 131 ]. Advances in technology may make it easier to automate certain aspects of nutritional assessment, reduce costs, and reduce respondent burden [ 132 , 133 ]. However, existing online nutritional applications tend to focus only on assessing the macronutrient and/or micronutrient intake and have often not been validated among athletes.

Food-based diet indices are a quick and inexpensive way to estimate food intake. These indices assess food intake and diet and compare them with dietary recommendations. An athlete’s diet index can provide an effective and practical way to assess the quality of their diet. A study [ 134 ] describes the development and validation of the athlete diet index (ADI). Accredited sports nutritionists in the current study determined that ADI is useful for quickly identifying athletes at risk or identifying dietary changes during exercise. The value of assessing the quality of diet and dietary habits, not just nutrient intake, along with the widespread use of electronic platforms in sports programs, opens up possibilities for this new electronic tool. However, while early results indicate that ADI is a less burdensome way of quickly assessing dietary quality and, therefore, may be beneficial for use on a broader population of athletes or as part of a team, it should not replace detailed dietary assessment or individual athlete guidance provided by sports nutrition specialists.

In addition, the development of valid and reliable questionnaires can provide a valid and reliable tool for assessing voluntary dietary restrictions on food choices, reasons for food refusal, and gastrointestinal symptoms among athletes and, consequently, to optimize their performance [ 135 , 136 ].

Despite a large number of recommendations and their availability, the question remains: How conscientiously are athletes ready to use them in practice? For example, in a study by Masson and Lamarche, it was shown that not all athletes involved in/-around endurance follow the carbohydrate dietary guidelines [ 137 ]. Another study highlighted the importance of training athletes in sports nutrition strategies, which requires an effective system for managing food and fluid needs to achieve their goals [ 84 ].

Therefore, current efforts require attention to improve the adaptability of the recommendations for athletes who require a specific training process. For example, there is a need to take cognizance of varying climatic conditions, type of training/competition, and individual characteristics. The development of dietary strategies with a personalized approach will help maximize training adaptability in the long term, potentially increasing performance in athletes.

7. Conclusions

This review highlights the factors that influence the eating behavior of athletes, the development of the market, providing services in this area, as well as the effectiveness of the recommendations developed. Health and weight control are important for athletes, but it is difficult to assess their effects on athletic performance. The condition of the athlete, the type of sport, the stage of the training period, and level of competition also play an important role in the choice of food.

The balance of macronutrients in the choice of food products requires further study in connection with the changing diet and quality of the athlete’s nutrition. These include non-homeostatic factors associated with the food environment, such as food marketing and restricted dietary practices that can suppress intrinsic signals associated with appetite and hunger.

Athletes follow special diets for a variety of reasons. GF, vegetarian, and lean diets are some of the most common diets adopted for health, ethical, religious, and industrial purposes. The prevalence of CD has increased dramatically, and GFD has become a popular approach to nutrition. A strict GFD for athletes with CD, WA, or GI will improve their health and may increase performance.

However, despite the many benefits of low FODMAP and GFD diets, these special diets are also associated with disturbed gut microbiota, short-chain fatty acid production [ 138 , 139 ], eating disorders, increased psychosocial anxiety, and decreased energy and nutrient intake [ 140 , 141 ].

Research into a new paradigm of immune health in athletes is focusing on tolerogenic nutritional supplements shown to reduce the risk of infection in athletes, such as probiotics, vitamin C, and vitamin D. Further research should demonstrate the benefits of tolerogenic supplementation in reducing infection in athletes without dulling training adaptation and without side effects [ 142 ].

Athletes train and compete in various settings, and a deeper understanding of this area can assist the practicing nutritionist with nutritional management and meal planning for athletes attending training facilities in various settings.

It is important to remember that food choices are dynamic, and their importance can vary with time, place, and changing situations in which athletes are choosing their food.

Author Contributions

Conceptualization, K.A.M., M.S.K.; formal analysis, A.A.I., T.V.B.; investigation, K.A.M., A.T.K.; writing—original draft preparation, K.A.M., A.A.S. (Alexander A. Stepanov), A.L.K.; writing—review and editing, A.A.S. (Alexandra A. Sinitsyna), K.C.; project administration, A.L.K. All authors have read and agreed to the published version of the manuscript.

This work was financed by the Ministry of Science and Higher Education of the Russian Federation within the framework of state support for the creation and development of World-Class Research Centers “Digital biodesign and personalized healthcare” No. 75-15-2020-913.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.


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    Among athletes, nutrition plays an important role since the regimen and composition of the diet are associated with success in sports [23,24].Concerns about weight and body shape strongly influence food choices for the general population [] and have a similar effect on athletes, where attempts to achieve their goals are associated with external data on physique, weight, and performance [].

  17. DFG's position paper on boosting food and nutrition research in Germany

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