Literature DB >> 34067248

A Novel Personalized Systems Nutrition Program Improves Dietary Patterns, Lifestyle Behaviors and Health-Related Outcomes: Results from the Habit Study.

Iris M de Hoogh1, Barbara L Winters2, Kristin M Nieman3, Sabina Bijlsma1, Tanja Krone1, Tim J van den Broek1, Barbara D Anderson4, Martien P M Caspers1, Joshua C Anthony5,6, Suzan Wopereis1.   

Abstract

Personalized nutrition may be more effective in changing lifestyle behaviors compared to population-based guidelines. This single-arm exploratory study evaluated the impact of a 10-week personalized systems nutrition (PSN) program on lifestyle behavior and health outcomes. Healthy men and women (n = 82) completed the trial. Individuals were grouped into seven diet types, for which phenotypic, genotypic and behavioral data were used to generate personalized recommendations. Behavior change guidance was also provided. The intervention reduced the intake of calories (-256.2 kcal; p < 0.0001), carbohydrates (-22.1 g; p < 0.0039), sugar (-13.0 g; p < 0.0001), total fat (-17.3 g; p < 0.0001), saturated fat (-5.9 g; p = 0.0003) and PUFA (-2.5 g; p = 0.0065). Additionally, BMI (-0.6 kg/m2; p < 0.0001), body fat (-1.2%; p = 0.0192) and hip circumference (-5.8 cm; p < 0.0001) were decreased after the intervention. In the subgroup with the lowest phenotypic flexibility, a measure of the body's ability to adapt to environmental stressors, LDL (-0.44 mmol/L; p = 0.002) and total cholesterol (-0.49 mmol/L; p < 0.0001) were reduced after the intervention. This study shows that a PSN program in a workforce improves lifestyle habits and reduces body weight, BMI and other health-related outcomes. Health improvement was most pronounced in the compromised phenotypic flexibility subgroup, which indicates that a PSN program may be effective in targeting behavior change in health-compromised target groups.

Entities:  

Keywords:  dietary intervention; healthy lifestyle; mixed meal tolerance test; personalized nutrition; systems biology

Year:  2021        PMID: 34067248     DOI: 10.3390/nu13061763

Source DB:  PubMed          Journal:  Nutrients        ISSN: 2072-6643            Impact factor:   5.717


  104 in total

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Authors:  Karen Glanz; Donald B Bishop
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Journal:  Health Psychol       Date:  2011-01       Impact factor: 4.267

3.  Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies.

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Journal:  Br J Nutr       Date:  2015-04-08       Impact factor: 3.718

Review 4.  Effects of low-fat compared with high-fat diet on cardiometabolic indicators in people with overweight and obesity without overt metabolic disturbance: a systematic review and meta-analysis of randomised controlled trials.

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Journal:  Br J Nutr       Date:  2017-12-07       Impact factor: 3.718

Review 5.  Comparison of effects of long-term low-fat vs high-fat diets on blood lipid levels in overweight or obese patients: a systematic review and meta-analysis.

Authors:  Lukas Schwingshackl; Georg Hoffmann
Journal:  J Acad Nutr Diet       Date:  2013-10-17       Impact factor: 4.910

6.  Evaluation of Worksite Wellness Nutrition and Physical Activity Programs and Their Subsequent Impact on Participants' Body Composition.

Authors:  Victoria Sandercock; Jeanette Andrade
Journal:  J Obes       Date:  2018-12-03

7.  Consensus Report of the Academy of Nutrition and Dietetics: Incorporating Genetic Testing into Nutrition Care.

Authors:  Andrea Braakhuis; Cathriona R Monnard; Amy Ellis; Mary Rozga
Journal:  J Acad Nutr Diet       Date:  2020-07-03       Impact factor: 4.910

8.  Improving diet, physical activity and other lifestyle behaviours using computer-tailored advice in general practice: a randomised controlled trial.

Authors:  Sanjoti Parekh; Corneel Vandelanotte; David King; Frances M Boyle
Journal:  Int J Behav Nutr Phys Act       Date:  2012-09-11       Impact factor: 6.457

Review 9.  The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis.

Authors:  Gareth J Hollands; David P French; Simon J Griffin; A Toby Prevost; Stephen Sutton; Sarah King; Theresa M Marteau
Journal:  BMJ       Date:  2016-03-15

Review 10.  A systematic review of the behaviour change techniques and digital features in technology-driven type 2 diabetes prevention interventions.

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Journal:  Digit Health       Date:  2020-03-24
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  1 in total

1.  Personalized optimal nutrition lifestyle for self obesity management using metaalgorithms.

Authors:  Shizhao Chen; Yiran Dai; Xiaoman Ma; Huimin Peng; Donghui Wang; Yili Wang
Journal:  Sci Rep       Date:  2022-07-20       Impact factor: 4.996

  1 in total

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