International Journal of Behavioral Nutrition and Physical Activity (Jun 2021)

Personalised nutrition advice reduces intake of discretionary foods and beverages: findings from the Food4Me randomised controlled trial

  • Katherine M. Livingstone,
  • Carlos Celis-Morales,
  • Santiago Navas-Carretero,
  • Rodrigo San-Cristobal,
  • Hannah Forster,
  • Clara Woolhead,
  • Clare B. O’Donovan,
  • George Moschonis,
  • Yannis Manios,
  • Iwona Traczyk,
  • Thomas E. Gundersen,
  • Christian A. Drevon,
  • Cyril F. M. Marsaux,
  • Rosalind Fallaize,
  • Anna L. Macready,
  • Hannelore Daniel,
  • Wim H. M. Saris,
  • Julie A. Lovegrove,
  • Mike Gibney,
  • Eileen R. Gibney,
  • Marianne Walsh,
  • Lorraine Brennan,
  • J. Alfredo Martinez,
  • John C. Mathers,
  • on behalf of the Food4Me Study

DOI
https://doi.org/10.1186/s12966-021-01136-5
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 12

Abstract

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Abstract Background The effect of personalised nutrition advice on discretionary foods intake is unknown. To date, two national classifications for discretionary foods have been derived. This study examined changes in intake of discretionary foods and beverages following a personalised nutrition intervention using these two classifications. Methods Participants were recruited into a 6-month RCT across seven European countries (Food4Me) and were randomised to receive generalised dietary advice (control) or one of three levels of personalised nutrition advice (based on diet [L1], phenotype [L2] and genotype [L3]). Dietary intake was derived from an FFQ. An analysis of covariance was used to determine intervention effects at month 6 between personalised nutrition (overall and by levels) and control on i) percentage energy from discretionary items and ii) percentage contribution of total fat, SFA, total sugars and salt to discretionary intake, defined by Food Standards Scotland (FSS) and Australian Dietary Guidelines (ADG) classifications. Results Of the 1607 adults at baseline, n = 1270 (57% female) completed the intervention. Percentage sugars from FSS discretionary items was lower in personalised nutrition vs control (19.0 ± 0.37 vs 21.1 ± 0.65; P = 0.005). Percentage energy (31.2 ± 0.59 vs 32.7 ± 0.59; P = 0.031), percentage total fat (31.5 ± 0.37 vs 33.3 ± 0.65; P = 0.021), SFA (36.0 ± 0.43 vs 37.8 ± 0.75; P = 0.034) and sugars (31.7 ± 0.44 vs 34.7 ± 0.78; P < 0.001) from ADG discretionary items were lower in personalised nutrition vs control. There were greater reductions in ADG percentage energy and percentage total fat, SFA and salt for those randomised to L3 vs L2. Conclusions Compared with generalised dietary advice, personalised nutrition advice achieved greater reductions in discretionary foods intake when the classification included all foods high in fat, added sugars and salt. Future personalised nutrition approaches may be used to target intake of discretionary foods. Trial registration Clinicaltrials.gov NCT01530139 . Registered 9 February 2012.

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