NEW STUDY SHOWS NOVEL PERSONALIZED SYSTEMS NUTRITION PROGRAM IMPROVES DIETARY PATTERNS, LIFESTYLE BEHAVIORS AND HEALTH-RELATED OUTCOMES | News Direct

NEW STUDY SHOWS NOVEL PERSONALIZED SYSTEMS NUTRITION PROGRAM IMPROVES DIETARY PATTERNS, LIFESTYLE BEHAVIORS AND HEALTH-RELATED OUTCOMES

Nlumn

facebook icon linkedin icon twitter icon pinterest icon email icon PRINCETON, NJ | July 21, 2021 09:00 AM Eastern Daylight Time

  • The Habit PATH (Personalized Approaches To Health) Study demonstrates that a Personalized Systems Nutrition program in a workforce environment improves dietary habits, health markers, physical activity and other health-related outcomes.
  • The Habit PATH Study helps validate a holistic approach to personal nutrition that:

    • Introduces a new approach that customizes nutrition systems according to an individual’s phenotypic flexibility assessment, which measures health according to their ability to adapt to a temporary nutritional stressor or an environmental challenge. This technology can identify potential health concerns to allow for early intervention and treatment.

    • Provides personal goal setting and motivational interviewing to affect behavioral change and improve an individual’s adherence to lifestyle intervention programs.

  • The Habit PATH Study suggests that personalized nutrition programs may provide the tools and motivation to enable individuals to meet their unique needs, achieve public health recommendations and improve health-related outcomes that may help reduce the health economic burden of chronic disease.

 Nlumn, LLC, a personalized nutrition and health company, announced health outcomes from a study of a novel Personalized Systems Nutrition program in the June 2021 issue of Nutrients. The peer-reviewed Habit PATH Study is the first to incorporate phenotypic flexibility technology in Personalized Systems Nutrition programs to improve the dietary patterns, lifestyle behaviors and health-related outcomes of individuals in a workplace environment.

“The Habit PATH Study shows that personalized science-based nutrition and behavior interventions have the potential to improve overall diet quality and health markers that could reduce the chronic disease burden and improve the overall state of health in the United States,” said Josh Anthony, Ph.D., Founder and CEO, Nlumn and co-author of the study. “The results suggest that a systems-based personalized nutrition approach, combining both biological and behavioral science, not only helps address an individual’s unique health needs, but also helps them achieve public health recommendations, including the Dietary Guidelines for Americans. Consequently, personalized approaches may be more effective in motivating people to achieve public health recommendations compared to general guidelines.”

Participants saw health changes that were consistent with public health recommendations including:

  • Saturated fat intake was reduced more than 20%. Total sugar and sodium intake were reduced by almost 20%. These changes are consistent with the 2020-2025 Dietary Guidelines Key Recommendations to limit specific nutrients.
  • Key nutrients such as potassium, fiber, magnesium, vitamin C and beta carotene increased, suggesting increased intake of fruit and vegetables.
  • While this was not designed to be a weight loss study, caloric intake decreased 13% and participants saw reduced body weight, BMI, hip circumference and a reduction in body fat. Physical activity also increased.
  • The most unhealthy participants reported a 10% reduction in total cholesterol and a 15% decrease in LDL (bad) cholesterol.

“This study shows that assessing health status by using phenotypic flexibility to direct personal nutrition recommendations enables positive lifestyle changes and health outcomes regardless of an individual’s level of health,” according to Iris M. de Hoogh, scientist, Netherlands Organization for Applied Scientific Research (TNO) and lead author of the study. “The application of TNO’s Phenotypic Flexibility Technology helps identify early health interventions that individuals can address with their healthcare professionals before the health concern becomes a significant issue.”

Anthony continued, “At a time when the U.S. is facing a multidimensional, multigenerational health crisis, and consumer demand for more nutritious food is at an all-time high, this study also helps verify the ability to use personalized subcategories to tailor food and product innovation pipelines in a meaningful way – thereby increasing the potential for long-term positive health benefits from personalized nutrition for food and insurance companies.” As part of this study, Personalized Systems Nutrition algorithms provided the employer’s food service partner with recommendations used to tailor breakfast and lunch options to align with study participants’ individual health needs.

HABIT Study Results:

Results of the study show that personalized nutrition programs are more effective for improving diet quality, supporting improved health-outcomes and may enable healthier lifestyle behaviors, particularly among individuals who have compromised phenotypic flexibility, a measure of the body’s ability to adapt to nutritional or environmental stressors, such as physical exercise, infections or mental stress.

During the HABIT Study 10-week personalized intervention, participants showed statistically significant results:

  • Dietary Indicators: Notable dietary improvements were observed between the intervention. Including a decrease in total and saturated fat, sugar and sodium, while showing improvements in vitamin C, magnesium, potassium, and beta carotene intake, suggesting a higher intake of fruits and vegetables.

Pre Intervention (SD)

Post Intervention (SD)

Difference (%)

p-Value

Calories (kcal)

1906 (537)

1650 (461)

-13.4

<0.001

Total Fat (g)

81.1 (25.5)

63.8 (21.5)

-21.3

<0.0001

Saturated Fat (g)

25.6 (9.2)

19.7 (7.2)

-22.9

<0.001

Polyunsaturated Fat (g)

12.1 (5.7)

10.7 (2.5)

-11.4

<0.01

Monounsaturated Fat (g)

21.4 (10.5)

17.6 (8.5)

-17.6

NS

Carbohydrates (g)

197.9 (70.6)

175.7 (56.0)

-11.2

<0.01

Sugar (g)

69.5 (36.0)

56.5 (27.7)

-18.7

<0.0001

Fiber (g)

17.4 (6.4)

19.1 (6.3)

+9.1

NS

Protein (g)

86.4 (22.6)

83.1 (25.4)

-3.8

NS

Sodium (mg)

2825 (908.)

2279 (886)

-19.3

<0.001

Potassium (mg)

1912 (756)

2240 (771)

+17.1

<0.05

Magnesium

197.2 (98.9)

245.0 (85.5)

+24.2

<0.01

Vitamin C (mg)

74.2 (50.9)

107.7 (62.5)

+45.3

<0.001

Beta Carotene (mcg)

2701 (3965)

4382 (3470)

+62.2

<0.0001

Notes: 73 participants were included in the per protocol analysis.

  • Health Indicators: During the intervention, participants received personalized dietary recommendations, coaching and personalized meals. Several health improvements were observed for the overall study population. While this was not designed to be a weight loss trial, BMI (-0.6 kg/m2; p<0.0001), body fat (-1.2%, p=0.0192) and hip circumference (-5.8 cm; p<0.0001) showed a significant decrease.
  • Subgroup Results: In reporting health measurements, the Habit Study’s automated Personalized Systems Nutrition algorithms assigned individuals to different subgroups based on their metabolic health status determined by phenotypic flexibility assessment at baseline. Groups A (n=48) and G (n=22) represented the most and least phenotypically flexible groups, respectively. Group G had a higher degree of adiposity, and a higher age than group A. However, there were no differences in baseline dietary intake and both groups were 82% compliant with personalized meal intake.

    • Clinical Chemistry (fasting): For group G, significant reductions in total cholesterol and LDL (“bad”) cholesterol were seen during the intervention.

Group A

Group G

Total Cholesterol (mmol/L)

-2%

-9.9%**

LDL Cholesterol (mmol/L)

-8.4%

-15.4%*

HDL Cholesterol (mmol/L)

+5.1%

-6.8%

Triglycerides (mmol/L)

+13.2%

+3.7%

C-peptide fasting (nmol/L)

-12.1%

-2.7%

C-peptide 2 h (nmol/L)

+1.9%

-9.7%

Glucose fasting (mmol/L)

+4.5%

+9%

Glucose 2 h (mmol/L)

+3.6%

+2.7%

There were 48 and 22 subjects in groups A and G, respectively. *p<0.01, **p<0.0001 Subgroup differences during the 10-week intervention.

  • Anthropometrics: During the intervention period, body weight significantly decreased in both group A (most healthy) and group G (least healthy).

Group A

Group G

BMI (kg/m2)****

-1.2%

-2.6%

Body weight (kg)

-1.2%*

-1.1**

Body fat (%)*

-2.3%

-0.9%

Muscle mass (kg)

-0.5%

-0.4%

Waist circumference (cm)

-0.6%

-0.2%

Hip circumference (cm)****

-1.6%

-3.1%

Systolic blood pressure (mmHg)

-2.8%

-2.9%

Diastolic blood pressure (mmHg)

-3.9%

-2.2%

Notes: At baseline, BMI, body weight, body fat, waist circumference and hip circumference were greater in group G compared to group A. Percentages were used to normalize differences between groups, but absolute changes were proportionately greater in group G given higher starting values. Statistically significant differences are noted in the last two columns for changes in the groups A or G respectively and in the first column for changes in the per protocol study population; (*p<0.05; **p<0.001; ****p<0.0001). Subgroup population size may have limited the ability to detect differences in some measures that were observed in the overall study (per protocol) population.

  • Dietary Indicators: When looking at subgroups A and G, the Personalized Systems Nutrition program not only improved adherence with population-based dietary guidelines, but also achieved better alignment with individual recommendations. For the unhealthiest group, G, different positive effects were seen with respect to dietary intake, consistent with their respective dietary recommendations. Protein and beta carotene intake increased in group G, but not in group A. The increase in protein intake can be directly related to the personalized advice for group G as they were recommended to consume a diet higher in protein relative to group A. The increase in beta carotene could be the result of a higher intake of fruits and vegetables.

The results suggest that personalized nutrition programs may be more effective in motivating people to consume a diet that meets individual needs while moving them closer to public health recommendations overall. As such, personalized nutrition programs have added value as compared to general guidelines or one-size fits all recommendations.

  • Physical Activity: The intervention resulted in an increase in physical activity within the study participants of more than 700 steps per day. This was accompanied by a small decrease in resting heart rate which could indicate improved physical fitness. This increase is interesting, since the intervention consisted only of dietary advice and participants did not receive recommendations on physical exercise. The increase in physical activity may be a beneficial side-effect of participating in a Personalized Systems Nutrition program.

HABIT Study Trial Design

The Habit Study enrolled 107 healthy men and women, aged 30 to 65 years of age, with a body mass index between 18.5 to 39.9 kg/m2, and who were recruited from a single workforce location. The intervention grouped individuals into seven diet types and created personalized recommendations based on their phenotypic, genotypic and behavioral data.

The HABIT study was a single-arm, multi-phased, open-label exploratory trial designed to measure the effectiveness of personalized nutrition on changing lifestyle behaviors and health outcomes during four intervention periods. These four periods were classified as:

  1. Baseline (week 0) and run-in (week 0 - 10)
  2. Intervention Phase 1 (week 10 - 20)
  3. Intervention Phase 2 personalized coaching/advice (week 20 - 30)
  4. Follow-up (week 30 - 40) endpoint visit only.

The publication focuses on the baseline through intervention Phase 1. As part of the study, participants received:

  • An At-Home Phenotypic Flexibility Test and Sample Collection for collecting buccal cells, a series of three dried blood spots (DBS) and DNA (baseline only) samples.
  • A Personalized Systems Nutrition Program designed by using individual on-boarding data, clinical measures and single nucleotide polymorphism (SNP) variants. Micronutrient recommendations were determined using onboarding, anthropometric and clinical measures. In addition, participants were provided with personalized recipes and meals according to their macro- and micronutrient recommendations.
  • Three personalized coaching sessions by registered dietitian nutritionists (RDN) who were trained on coaching techniques and the algorithms supporting the Personalized Systems Nutrition system. These RDNs provided food and diet recommendations, helped motivated participants and coached them in setting and achieving personal goals.
  • Study meals and compliance diaries. Starting at week 10, participants received tailored breakfast and lunch five days a week for nine weeks.
  • Activity measurement. At the start of the trial, each participant was given a Fitbit® to measure and record their activity level.

Approximately every five weeks participants would visit the study center to be tested and have data collected on:

  • Clinical markers: Regular laboratory tests were conducted to track total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, glucose, C-peptide, and the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and Matsuda indices measuring whole body insulin sensitivity.
  • Dietary Intake: Using a standard dietary record methodology, participants tracked their food and beverages consumed for three days (two weekdays and one weekend day) prior to all visits.
  • Anthropometrics and Vitals: During each visit, anthropometrics--height (first visit only), weight, fat mass, waist and hip circumference--and blood pressure were measured.
  • Wellbeing and Lifestyle: Participants’ dietary behavior was assessed using the 34-item Adult Eating Behaviors Questionnaire and their Quality of Life using the 26-item World Health Organization Quality of Life (WHOQOL) questionnaire. Their daily activity and sleep were tracked with a Fitbit Charge 2 which monitored heart rate, number of steps and sleeping hours.

About Personalized Systems Nutrition

 Personalized Nutrition is the use of individual-specific information, founded in evidence-based science, to promote dietary behavior change that may result in measurable health benefits. Personalized Systems Nutrition incorporates novel Phenotypic Flexibility Technology that customizes diets according to an individual’s phenotypic flexibility allowing them to measure their health according to their biological system’s ability to adapt to conditions of temporary stressors, such as a nutrition challenge, physical exercise, infections or mental stress. This technology helps identify potential early health interventions that individuals can address with their healthcare professionals before it becomes a significant health issue. By combining systems-based approaches to understanding a person’s biology and behavior science, Personalized Systems Nutrition programs are able to create significant and sustainable changes in a person’s health and wellness.

About Nlumn

Nlumn works with food, nutrition and health-based companies to translate nutrition science and technology to create new opportunities across the personalized nutrition marketplace. Our international, multidisciplinary team guides partners through all phases of strategy and development to accelerate the pace of innovation, from discovery to commercialization. Our mission is to make personalized nutrition accessible to help every individual make better choices and live a healthier life. For more information, visit www.nlumn.com.

About TNO

TNO (Netherlands Organization for Applied Scientific Research) is a not-for-profit research organization with the mission to connect people and knowledge to create innovations that boost the competitive strength of industry and the well-being of society in a sustainable way. TNO’s Healthy Living unit develops social and technological innovations to help people lead healthier lives and reduce lifestyle-related chronic diseases. TNO developed the phenotypic flexibility technology that was instrumental in the Habit PATH study. For more information, visit https://www.tno.nl/en/focus-areas/healthy-living/.

 

Contact Details

 

AgTech PR for Nlumn

 

Jennifer Goldston

 

+1 816-260-0040

 

jennifer@agtechpr.com

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Tags

nutritionhealthdietary habitsphenotypic flexiblitypersonalized nutritionHabit PATH StudyNlumnTNOPersonalized Systems NutritionJosh Anthonyfood innovation
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