1.
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
-
-
-
Free full text
Plain language summary
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.
2.
Assessment of the Effectiveness of a Computerised Decision-Support Tool for Health Professionals for the Prevention and Treatment of Childhood Obesity. Results from a Randomised Controlled Trial.
Moschonis, G, Michalopoulou, M, Tsoutsoulopoulou, K, Vlachopapadopoulou, E, Michalacos, S, Charmandari, E, Chrousos, GP, Manios, Y
Nutrients. 2019;11(3)
-
-
-
Free full text
Plain language summary
Obesity is related to the increased risk for chronic diseases and to nutrient insufficiencies, a paradox that has been characterised as the “double burden of malnutrition”. The aim of this study was to examine the effectiveness of a computerised decision-support tool as a means of childhood obesity management. The effectiveness of the decision-support tool was assessed through a pilot randomised controlled intervention trial. The study recruited a total sample of 80 children (obese or overweight) with an age range between 6 and 12 years. The participants were allocated to two study groups – intervention group and control group. Results indicate that a computerised decision-support tool, designed to assist paediatric healthcare professionals in providing personalised nutrition and lifestyle optimisation recommendations to overweight or obese children and their parents, can result in favourable changes to certain dietary intake and anthropometric indices in the children that received the intervention. Authors conclude that the computerised decision-support tool resulted in improvement of the children’s dietary intake and body mass index. Hence, the tool can support clinicians to improve the effectiveness of care.
Abstract
We examined the effectiveness of a computerised decision-support tool (DST), designed for paediatric healthcare professionals, as a means to tackle childhood obesity. A randomised controlled trial was conducted with 65 families of 6⁻12-year old overweight or obese children. Paediatricians, paediatric endocrinologists and a dietitian in two children's hospitals implemented the intervention. The intervention group (IG) received personalised meal plans and lifestyle optimisation recommendations via the DST, while families in the control group (CG) received general recommendations. After three months of intervention, the IG had a significant change in dietary fibre and sucrose intake by 4.1 and -4.6 g/day, respectively. In addition, the IG significantly reduced consumption of sweets (i.e., chocolates and cakes) and salty snacks (i.e., potato chips) by -0.1 and -0.3 portions/day, respectively. Furthermore, the CG had a significant increase of body weight and waist circumference by 1.4 kg and 2.1 cm, respectively, while Body Mass Index (BMI) decreased only in the IG by -0.4 kg/m². However, the aforementioned findings did not differ significantly between study groups. In conclusion, these findings indicate the dynamics of the DST in supporting paediatric healthcare professionals to improve the effectiveness of care in modifying obesity-related behaviours. Further research is needed to confirm these findings.