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Personalised nutrition advice reduces intake of discretionary foods and beverages: findings from the Food4Me randomised controlled trial.
Livingstone, KM, Celis-Morales, C, Navas-Carretero, S, San-Cristobal, R, Forster, H, Woolhead, C, O'Donovan, CB, Moschonis, G, Manios, Y, Traczyk, I, et al
The international journal of behavioral nutrition and physical activity. 2021;18(1):70
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Food4Me is an internet-based personalised nutrition study that evaluates the effectiveness of personalized dietary advice in avoiding discretionary foods compared to conventional advice. In different countries, discretionary foods are classified differently. Therefore, this study included two measures of discretionary foods identified by the Food4Me Food Frequency Questionnaire, which covered 22 discretionary foods classified by Food Standards Scotland and 59 discretionary foods identified by Australian Dietary Guidelines. For six months, 1607 participants from seven European countries were randomly assigned to receive generalised dietary advice or one of three levels of personalised nutrition advice (based on diet [L1], phenotype [L2] and genotype [L3]). Personalised nutrition advice was found to be effective in reducing discretionary foods when categorisation included foods high in fat, added sugar and salt. There was a greater reduction in energy, sugar, salt, and saturated fat intakes in people who received personalised nutrition advice [L1-3] as compared to generalised dietary advice after six months. Results of this study can be used by healthcare professionals to support personalised nutrition strategies in the general population targeting discretionary foods to increase compliance with personalised nutrition strategies and achieve better health outcomes.
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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Food sources of fructose-containing sugars and glycaemic control: systematic review and meta-analysis of controlled intervention studies.
Choo, VL, Viguiliouk, E, Blanco Mejia, S, Cozma, AI, Khan, TA, Ha, V, Wolever, TMS, Leiter, LA, Vuksan, V, Kendall, CWC, et al
BMJ (Clinical research ed.). 2018;363:k4644
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With increasing evidence linking fructose to metabolic disease, current dietary guidelines recommend a reduction of added free sugars, especially fructose-containing sugars from sugars-sweetened beverages (SSBs). However, it is currently unclear whether the negative impact of fructose on metabolic health is as implicative in the context of an overall dietary consumption pattern. The aim of this study was to assess the effect of different sources of fructose-containing sugars on glycaemic control in people with and without diabetes. This review analysed 155 controlled intervention studies and found that fructose-containing sugars in the form of fruit do not have a harmful effect on glycaemic control when compared to energy-matched macronutrient substitutions. Further, harmful effects on glycaemic control were found when excess energy in the form of fructose-containing sugars from SSBs were added to the diet. The authors conclude the food source of fructose-containing sugars on glycemic control is important in the conversation of metabolic health and glycaemic control. While further research is needed to assess a wider variety of food sources, public health professionals should consider the influence of food sources when developing dietary recommendations for the prevention and management of diabetes and other metabolic conditions.
Abstract
OBJECTIVE To assess the effect of different food sources of fructose-containing sugars on glycaemic control at different levels of energy control. DESIGN Systematic review and meta-analysis of controlled intervention studies. DATA SOURCES Medine, Embase, and the Cochrane Library up to 25 April 2018. ELIGIBILITY CRITERIA FOR SELECTING STUDIES Controlled intervention studies of at least seven days' duration and assessing the effect of different food sources of fructose-containing sugars on glycaemic control in people with and without diabetes were included. Four study designs were prespecified on the basis of energy control: substitution studies (sugars in energy matched comparisons with other macronutrients), addition studies (excess energy from sugars added to diets), subtraction studies (energy from sugars subtracted from diets), and ad libitum studies (sugars freely replaced by other macronutrients without control for energy). Outcomes were glycated haemoglobin (HbA1c), fasting blood glucose, and fasting blood glucose insulin. DATA EXTRACTION AND SYNTHESIS Four independent reviewers extracted relevant data and assessed risk of bias. Data were pooled by random effects models and overall certainty of the evidence assessed by the GRADE approach (grading of recommendations assessment, development, and evaluation). RESULTS 155 study comparisons (n=5086) were included. Total fructose-containing sugars had no harmful effect on any outcome in substitution or subtraction studies, with a decrease seen in HbA1c in substitution studies (mean difference -0.22% (95% confidence interval to -0.35% to -0.08%), -25.9 mmol/mol (-27.3 to -24.4)), but a harmful effect was seen on fasting insulin in addition studies (4.68 pmol/L (1.40 to 7.96)) and ad libitum studies (7.24 pmol/L (0.47 to 14.00)). There was interaction by food source, with specific food sources showing beneficial effects (fruit and fruit juice) or harmful effects (sweetened milk and mixed sources) in substitution studies and harmful effects (sugars-sweetened beverages and fruit juice) in addition studies on at least one outcome. Most of the evidence was low quality. CONCLUSIONS Energy control and food source appear to mediate the effect of fructose-containing sugars on glycaemic control. Although most food sources of these sugars (especially fruit) do not have a harmful effect in energy matched substitutions with other macronutrients, several food sources of fructose-containing sugars (especially sugars-sweetened beverages) adding excess energy to diets have harmful effects. However, certainty in these estimates is low, and more high quality randomised controlled trials are needed. STUDY REGISTRATION Clinicaltrials.gov (NCT02716870).