Session/Event: Novel Approaches for Improving Public Health Through Better Nutrition (Oral 5)

(OR05-01-22) A Randomized Clinical Trial to Compare a Precision Nutrition Intervention Targeting a Reduction in Postprandial Glycemic Response to Meals With a Low-Fat Diet for Weight Loss

On Demand

Presenting Author(s)

CP

Collin Popp, PhD, MS, RD

Program Manager
NYU Langone Health
New York, New York, United States

Disclosure: Disclosure(s): Renaissance Periodization LLC: Consultant (Ongoing)

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Co-Author(s)

LH

Lu Hu, RN, PhD

Assistant Professor
NYU Langone Health
New York, New York, United States
CW

Chan Wang, PhD

NYU
new york, New York, United States
MC

Margaret Curran, MS

Project Coordinator
NYU Langone Health
Astoria, New York, United States
HL

Huilin Li, PhD

Associate Professor
NYU School of Medicine
New York, New York, United States
AK

Anna Kharmats

New York University Langone Health
LT

Lauren Thomas

New York University Langone Health
MP

Mary Lou Pompeii, RD, CDE, CDN

Research Dietitian
NYU Langone Health
New York, New York, United States
MM

Meredith Mottern, BS

Research Data Associate
New York University Langone Health, New York, United States
AP

Antonia Polyn

New York University Langone Health
AS

Antoinette Schoenthaler, EdD

NYU
new york, New York, United States
DS

David E. St-Jules, PhD, RD

University of Nevada, Reno
New York, New York, United States
NW

Natasha Williams, EdD

NYU
new york, New York, United States
AG

Anastasia Godnev

Weizmann Institute of Science
Eran Segal, PhD

Professor and Principal Investigator
Weizmann Institute of Science
Ramat Hasharon, Israel
MB

Michael Bergman

New York University Langone Health
MS

Mary Ann Sevick, ScD

Professor
NYU Langone Health
New York, New York, United States

Objectives: The primary aim is to compare the effects of a low-fat diet vs a personalized diet on percent weight loss at 6-months. Secondary outcomes include body composition (fat mass [FM] and fat free mass [FFM]), resting energy expenditure (REE) and adaptive thermogenesis (AT).

Methods: The Personal Diet Study was a 6-month, single-center, randomized clinical trial in adults with pre-diabetes and moderately controlled type 2 diabetes who were overweight or obese. Participants were randomized to follow either a hypocaloric low-fat diet, with < 25% energy intake from total fat (Standardized), or a hypocaloric personalized diet determined by a machine learning algorithm which predicts PPGR to meals (Personalized). Participants in both arms received behavioral counseling and logged dietary intake and physical activity into a smartphone app. Participants in the Personalized arm received real-time feedback as color-coded scores based on pre-consumed meals entered into the smartphone app. T-tests were used to assess group differences.

Results: A total of 200 adults (Standardized: n=97 vs. Personalized: n=103) contributed data (mean [SD]: age, 58 [11] years; 67% female; BMI, 34.0 [4.8] kg/m²; HbA1c, 5.8 [0.6]%; Metformin use, 21.0%). There were no significant group differences in mean percent weight loss (Standardized: -4.4 [4.8]% vs Personalized: -3.3 [5.4]%; p=0.19), mean absolute change in FM (Standardized: -2.7 [3.4] kg vs. Personalized: -1.6 [3.5] kg; p=0.18), and AT between the two arms (Standardized: -54.7 [177] kcal/d vs. Personalized: 26.2 [199] kcal/d; p=0.078). However, the Standardized arm lost significantly more FFM (-1.4 [1.6] kg vs. -0.45 [2.0] kg; p=0.03) and had a greater decrease in REE (-111.0 [195.0] kcal/d vs. 1.93 [215.0] kcal/d; p=0.02) compared to Personalized.

Conclusions: A personalized diet to minimize PPGR had no greater effect on percent weight loss compared to a low-fat diet at 6-months. Future precision nutrition trials may require deeper phenotyping of individuals or the development of body weight-specific algorithms.

Funding Sources: Supported by grants from the American Heart Association 17SFRN33590133