Meal Effects on Nutrient Tracking

(Microdialysis Trial)

Overseen By Raven McNew, PhD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Texas A&M University

Must not be taking: Anticoagulants

Disqualifiers: Malignancy, Diabetes, Metabolic diseases, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 5

33 Participants Needed

Trial Summary

Do I need to stop taking my current medications for the trial?

The trial does not specify if you need to stop taking your current medications, but you cannot participate if you are currently on anticoagulants (blood thinners).

What data supports the effectiveness of the treatment Meal set A, Meal set B, Meal set C, Meal set D?

Research shows that improving meal services in hospitals can enhance dietary intake and patient satisfaction, which may suggest that structured meal sets like Meal set A, B, C, and D could be effective in tracking and improving nutrient intake. ^{1 2 3 4 5}

How does the treatment in the 'Meal Effects on Nutrient Tracking' trial differ from other treatments for nutrient tracking?

This treatment is unique because it focuses on tracking nutrient intake at the level of individual meals rather than just overall dietary patterns or individual nutrients. This approach may provide more detailed insights into how specific meals contribute to overall diet quality and nutrient intake. ^{6 7 8 9 10}

What is the purpose of this trial?

The goal of this clinical trial is to establish the relationship between macronutrient food intake and the resulting blood and intersticial fluid (ISF )levels of small molecule markers, as well as, validate wearable optical readers and data fusion algorithms to accurately predict individual-specific macronutrient availability in real time. The study involves 1 screening visit of approximately 2 hours and up to 4 study days of approximately 14 hours. Subjects will be asked to arrive in the fasted state on all study days. Fasting prior to screening is not required. On the screening visit, body weight, height, and body composition by Dual-energy X-ray absorptiometry (DXA) will be measured. In addition, habitual dietary intake, physical activity level (PASE), and quality of life (SGRQ-C) will be assessed.

Research Team

Nicolaas E Deutz, Ph.D.

Principal Investigator

Texas A&M University

Michael McShane, PhD

Principal Investigator

Texas A&M University

Eligibility Criteria

This trial is for individuals with diabetes and issues with amino acid metabolism. Participants should be willing to fast before study days, undergo body measurements like weight and height, and have their diet, physical activity, and quality of life assessed.

Inclusion Criteria

I can walk, sit, and stand on my own.

I am between 50 and 75 years old.

I can lie on my back or slightly raised for about 13 hours.

Exclusion Criteria

I have been diagnosed with diabetes.

I have never been treated for liver or kidney diseases.

I am currently taking blood thinners.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2 hours

1 visit (in-person)

Study Days

Participants undergo study procedures including blood sampling and meal consumption

Up to 14 hours per study day

Up to 4 visits (in-person)

Follow-up

Participants are monitored for safety and effectiveness after study days

4 weeks

Treatment Details

Interventions

• Meal set A
• Meal set B
• Meal set C
• Meal set D

Trial Overview The trial aims to link the intake of specific macronutrients (proteins, fats, carbohydrates) in meals to changes in blood markers. It tests if wearable devices can track these nutrients effectively by using four different meal sets labeled A through D.

Participant Groups

Group I: Healthy male older adults Experimental Treatment 4 Interventions

Eight predefined, commercially available meal is administered in a randomized fashion. Two meals are consumed 6 hours apart on each study day. Meals are selected to represent a range of fat, protein, and carbohydrate content.

Group II: Healthy female older adults Experimental Treatment 4 Interventions

Eight predefined, commercially available meal is administered in a randomized fashion. Two meals are consumed 6 hours apart on each study day. Meals are selected to represent a range of fat, protein, and carbohydrate content.

Who Is Running the Clinical Trial?

Texas A&M University

Lead Sponsor

Trials

156

Recruited

28,900+

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

Collaborator

Trials

2,513

Recruited

4,366,000+

Findings from Research

In a study involving 107,106 hospitalized patients, nearly 90% were screened for malnutrition risk within 24 hours of admission, but only about 14% of those identified as at risk were diagnosed with malnutrition.

The use of a web-based quality improvement tool showed potential in capturing nutrition care practices, highlighting a significant gap between screening for malnutrition and providing adequate discharge recommendations for at-risk patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Assessment of the Nutrition Care Process in US Hospitals Using a Web-Based Tool Demonstrates the Need for Quality Improvement in Malnutrition Diagnosis and Discharge Care. Sherry, CL., Sauer, AC., Thrush, KE.[2020]

Implementing a co-designed mealtime assistance process in a 31-bed ward led to a significant reduction in wasted meals from an average of 3 per day to 0, which also decreased food waste by 0.43 kg per patient daily.

Patients who received mealtime assistance showed no new incidences of aspiration pneumonia or swallowing difficulties, indicating that the intervention not only improved meal access but also enhanced patient safety and nutritional outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Reducing risk of development or exacerbation of nutritional deficits by optimizing patient access to mealtime assistance. Teeling, SP., Coetzee, H., Phillips, M., et al.[2020]

A nutrition-focused quality improvement program for malnourished hospitalized patients significantly reduced 30-day readmissions and hospital length of stay, leading to substantial cost savings of nearly $1.9 million compared to the baseline cohort.

The program demonstrated a per-patient net savings of $1,499 and $3,858 when comparing different cohorts, highlighting the economic benefits of integrating nutrition interventions into patient care to enhance outcomes and reduce healthcare costs.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Budget Impact of a Comprehensive Nutrition-Focused Quality Improvement Program for Malnourished Hospitalized Patients. Sulo, S., Feldstein, J., Partridge, J., et al.[2021]

The novel FoodforCare meal service significantly improved protein and energy intake among patients compared to the traditional meal service, with notable increases in intake on both the first and fourth days of full oral intake.

Patient satisfaction with the meal service remained stable, but the FoodforCare group reported better satisfaction regarding the appearance and smell of the meals, indicating a positive reception of the new service.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[A novel in-hospital meal service improves protein and energy intake]. Dijxhoorn, DN., van den Berg, MGA., Drenth, JPH., et al.[2018]

Patients identified as at nutritional risk during hospitalization had significantly worse outcomes, including longer hospital stays, higher readmission rates, and increased mortality compared to those not at risk, based on a study of 318 patients.

Increased energy and protein intake during hospitalization was associated with lower mortality rates in at-risk patients, highlighting the importance of nutritional care in improving health outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

"More2Eat" in patients at nutritional risk during hospital stay lowers the risk of three-month mortality. Mikkelsen, S., Tobberup, R., Skadhauge, LB., et al.[2023]

A new meal coding system was successfully applied to analyze dietary intake data from 242 Japanese adults, revealing 80 common generic meals and 11 distinct meal patterns, which accounted for 39.1% of total meal variance.

The study showed that this meal coding system can effectively estimate food and nutrient intakes, providing a foundation for developing simpler dietary assessment tools that reflect habitual eating behaviors.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Applying a meal coding system to 16-d weighed dietary record data in the Japanese context: towards the development of simple meal-based dietary assessment tools. Murakami, K., Livingstone, MBE., Sasaki, S., et al.[2019]

This review analyzed 34 studies on meal patterns in adults, revealing that skipping breakfast is consistently linked to lower diet quality, highlighting the importance of this meal for overall nutrition.

There is a lack of consensus on how to define meals and meal patterns, which affects the understanding of their relationship with nutrient intake and diet quality, suggesting a need for standardized definitions in future research.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Understanding meal patterns: definitions, methodology and impact on nutrient intake and diet quality. Leech, RM., Worsley, A., Timperio, A., et al.[2018]

In a study involving 19 adults over 8 weeks, providing breakfast foods in single-serving packages led to a significant reduction in energy intake compared to nonportioned packages, with participants consuming fewer calories from cereal and applesauce.

The results indicate that single-serving packaging can be an effective strategy to help control energy intake during breakfast, which may support weight-loss efforts in behavioral programs.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Do food provisions packaged in single-servings reduce energy intake at breakfast during a brief behavioral weight-loss intervention? Raynor, HA., Van Walleghen, EL., Niemeier, H., et al.[2021]

In a study of 639 adults in Japan, dinner was found to have the highest nutritional quality, followed by lunch, breakfast, and snacks, indicating that meal timing may influence overall diet quality.

Specific foods were predominantly consumed at certain meals, with dinner featuring a variety of nutrient-rich foods like vegetables and fish, while breakfast was more focused on bread and dairy, suggesting that meal composition can significantly impact nutrient intake.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Characterisation of breakfast, lunch, dinner and snacks in the Japanese context: an exploratory cross-sectional analysis. Murakami, K., Shinozaki, N., Livingstone, MBE., et al.[2023]

A study comparing nutrient intake calculations from five popular nutrition tracking apps with a research-grade dietary analysis software (NDSR) found that the apps generally reported lower nutrient values, including protein, fat, sodium, and cholesterol.

Correlations between the apps and NDSR were strong for energy and macronutrients (0.73 to 0.96), but significant discrepancies were noted for specific nutrients, indicating that while the apps can be useful, they may underestimate actual nutrient intake.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. Griffiths, C., Harnack, L., Pereira, MA.[2023]

References

1. United States pubmed.ncbi.nlm.nih.gov

Assessment of the Nutrition Care Process in US Hospitals Using a Web-Based Tool Demonstrates the Need for Quality Improvement in Malnutrition Diagnosis and Discharge Care. [2020]

2. England pubmed.ncbi.nlm.nih.gov

Reducing risk of development or exacerbation of nutritional deficits by optimizing patient access to mealtime assistance. [2020]

3. United States pubmed.ncbi.nlm.nih.gov

Budget Impact of a Comprehensive Nutrition-Focused Quality Improvement Program for Malnourished Hospitalized Patients. [2021]

4. Netherlands pubmed.ncbi.nlm.nih.gov

[A novel in-hospital meal service improves protein and energy intake]. [2018]

5. England pubmed.ncbi.nlm.nih.gov

"More2Eat" in patients at nutritional risk during hospital stay lowers the risk of three-month mortality. [2023]

6. England pubmed.ncbi.nlm.nih.gov

Applying a meal coding system to 16-d weighed dietary record data in the Japanese context: towards the development of simple meal-based dietary assessment tools. [2019]

7. England pubmed.ncbi.nlm.nih.gov

Understanding meal patterns: definitions, methodology and impact on nutrient intake and diet quality. [2018]

8. United States pubmed.ncbi.nlm.nih.gov

Do food provisions packaged in single-servings reduce energy intake at breakfast during a brief behavioral weight-loss intervention? [2021]

9. England pubmed.ncbi.nlm.nih.gov

Characterisation of breakfast, lunch, dinner and snacks in the Japanese context: an exploratory cross-sectional analysis. [2023]

10. England pubmed.ncbi.nlm.nih.gov

Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. [2023]