Towards a healthy diet: from nutrition recommendations to dietary advice.
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ABSTRACT:
SUBMITTER: Andersson A
PROVIDER: S-EPMC2606986 | biostudies-other | 2007 Mar
REPOSITORIES: biostudies-other
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Project description:Personalized nutrition (PN) behavior-change interventions are being used increasingly in attempts to improve dietary intake; however, the impact of PN advice on improvements in dietary intake has not been reviewed systematically. The aim of this systematic review was to evaluate the effect of PN advice on changes in dietary intake compared with generalized advice in healthy adults. Three databases (EMBASE, PubMed, and CINAHL) were searched between 2009 and 2020 for randomized controlled trials (RCTs) that tested the effect of PN and tailored advice based on diet, phenotype, or genetic information. The Evidence Analysis Library Quality Criteria checklist was used to conduct a risk-of-bias assessment. Information on intervention design and changes in nutrients, foods, and dietary patterns was extracted from the 11 studies meeting the inclusion criteria. Studies were conducted in the United States, Canada, or Europe; reported outcomes on 57 to 1488 participants; and varied in follow-up duration from 1 to 12 mo. Five studies incorporated behavior-change techniques. The risk of bias for included studies was low. Overall, the available evidence suggests that dietary intake is improved to a greater extent in participants randomly assigned to receive PN advice compared with generalized dietary advice. Additional well-designed PN RCTs are needed that incorporate behavior-change techniques, a broader range of dietary outcomes, and comparisons between personalization based on dietary, biological, and/or lifestyle information.
| S-EPMC8166555 | biostudies-literature
Project description:ObjectiveA high-fibre diet is associated with a lower risk for diseases. However, few adults meet the dietary fibre recommendation. Therefore, the effects and acceptance of an algorithm-generated personalised dietary advice (PDA) compared with general advice (GA) on fibre intake were investigated.DesignA 6-week, single-blind randomised controlled trial with a 3-month follow-up.SettingPDA was based on habitual intake and provided fibre-rich alternatives using a website; GA contained brochures. Dietary intake was assessed at baseline, week 1, week 6 and 3-month follow-up. Both groups evaluated their advice at week 6. All participants had access to PDA from week 7 until 3-month follow-up.ParticipantsTwo groups of healthy adults: PDA (n 34) and GA (n 47). For 3-month follow-up analysis, participants were re-divided into visitors (n 52) and non-visitors (n 26) of the PDA.ResultsAt week 6, energy intake remained stable in both groups, but fibre intake per 1000 kcal increased non-significantly in both groups (PDA = Δ0·5 ± 2·8; GA = Δ0·8 ± 3·1, P = 0·128). Importantly, a significantly higher percentage of PDA participants adhered to the recommendation compared with week 1 (PDA = 21 % increase; GA = 4 % increase, P ≤ 0·001). PDA participants evaluated the advice significantly better compared with GA participants. At 3-month follow-up, fibre intake increased compared with baseline (visitors = Δ2·2 ± 2·6, P < 0·001; non-visitors = Δ1·5 ± 1·9, P = 0·001), but was insignificantly different between groups. Visitors had a decrease and non-visitors had an increase in energy intake (visitors =Δ - 132 ± 525; non-visitors = Δ109 ± 507, P = 0·055).ConclusionsThe algorithm-generated PDA was well accepted and stimulated adherence to the recommendations more than GA, indicating to be a suitable and cost-efficient method for improving dietary fibre intake in healthy adults.
| S-EPMC8025104 | biostudies-literature
Project description:Background: Dietary intake is linked to numerous modifiable risk factors of cardiovascular disease. Current dietary recommendations in the UK to reduce the risk of cardiovascular disease are not being met. A genotype-based personalised approach to dietary recommendations may motivate individuals to make positive changes in their dietary behaviour. Aim: To determine the effect of a personalised nutrition intervention, based on apolipoprotein E (ApoE, rs7412; rs429358) and methylenetetrahydrofolate reductase (MTHFR, rs1801133) genotype, on reported dietary intake of saturated fat and folate in participants informed of a risk genotype compared to those informed of non-risk genotype. Methods: Baseline data (n = 99) were collected to determine genotype (non-risk vs risk), dietary intake and cardiovascular risk (Q-Risk®2 cardiovascular risk calculator). Participants were provided with personalised nutrition advice via email based on their ApoE and MTHFR genotype and reported intake of folate and saturated fat. After 10 days, dietary intake data were reported for a second time. Results: Personalised nutrition advice led to favourable dietary changes, irrespective of genotype, in participants who were not meeting dietary recommendations at baseline for saturated fat (p < 0.001) and folate (p = 0.002). Only participants who were informed of a risk ApoE genotype met saturated fat recommendations following personalised nutrition advice. Conclusion: Incorporation of genotype-based personalised nutrition advice in a diet behaviour intervention may elicit favourable changes in dietary behaviour in participants informed of a risk genotype. Participants informed of a non-risk genotype also respond to personalised nutrition advice favourably but to a lesser extent.
| S-EPMC9379385 | biostudies-literature
Project description:Multifaceted community interventions directed at improving food environments are emerging, but their impact on dietary change and obesity prevalence has not been adequately documented. The Healthy Communities Study (HCS) is seeking to identify characteristics and combinations of programs and policies that are associated with children's diets and obesity-related outcomes in various types of communities across the U.S. The purpose of this paper is to describe the methods used in 2013-2015 in the HCS to assess dietary intake, school nutrition environments, and other nutrition-related behaviors. The conceptual framework of the HCS is based on the socioecological model and behaviors shown in previous studies to be related to obesity in children guided selection of domains. Nine domains were identified as essential measures of nutrition in the HCS: (1) intake of selected foods and beverages; (2) food patterns and behaviors; (3) social support; (4) home environment; (5) school environment; (6) community environment; (7) breastfeeding history; (8) household food insecurity; and (9) dieting behaviors and body image. Children's dietary intake was assessed using a dietary screener and up to two automated 24-hour recalls. Dietary-related behaviors were assessed by a survey administered to the parent, child, or both, depending on child age. School nutrition measures were obtained from a combination of school staff surveys and researcher observations. Information from these measures is expected to contribute to a better understanding of "what is working" to improve the dietary behaviors that are likely to prevent obesity and improve health in children.
| S-EPMC4575770 | biostudies-literature
Project description:The current health status of the general public can substantially benefit from a healthy diet. Using a personalized approach to initiate healthy dietary behavior seems to be a promising strategy, as individuals differ in terms of health status, subsequent dietary needs, and their desired behavior change support. However, providing personalized advice to a wide audience over a long period is very labor-intensive. This bottleneck can possibly be overcome by digitalizing the process of creating and providing personalized advice. An increasing number of personalized advice systems for different purposes is becoming available in the market, ranging from systems providing advice about just a single parameter to very complex systems that include many variables characterizing each individual situation. Scientific background is often lacking in these systems. In designing a personalized nutrition advice system, many design questions need to be answered, ranging from the required input parameters and accurate measurement methods (sense), type of modeling techniques to be used (reason), and modality in which the personalized advice is provided (act). We have addressed these topics in this viewpoint paper, and we have demonstrated the feasibility of setting up an infrastructure for providing personalized dietary advice based on the experience of 2 practical applications in a real-life setting.
| S-EPMC10131983 | biostudies-literature
Project description:BackgroundThere is a need for a feasible, user-friendly tool that can be employed to assess the overall quality of the diet in U.S.Clinical settingsOur objectives were to develop the Penn Healthy Diet (PHD) screener, evaluate screener item correlations with Healthy Eating Index (HEI)-2015 components, and develop a simple scoring algorithm.MethodsNational Health and Nutrition Examination Survey (NHANES) 2017-18 dietary recall data in adults were used to define food examples in screener food groups based on components of the HEI-2015, Diet Approach to Stop Hypertension, and Alternative Mediterranean diet approaches. Instrument Content Validity Index (I-CVI) was used to evaluate the clarity and relevance of the screener. Patient acceptability was evaluated by completion time and response rates. NHANES 2017-18 food recall data were used to simulate responses to the screener items, which were evaluated for association with HEI-2015 components. A scoring algorithm was developed based on screener items moderately or strongly associated with HEI-2015 components. Reproducibility was tested using NHANES 2015-16 data.ResultsThe screener had strong clarity (I-CVI = 0.971) and relevance for nutrition counseling (I-CVI = 0.971). Median (IQR) completion time was 4 (3-5) minutes on paper and 4 (4-8) minutes online, and 73% of patients invited online completed the survey. Based on simulated NHANES participant screener responses, 15 of the 29 screener items were moderately or strongly associated with HEI-2015 components, forming the basis of the scoring algorithm with a range of 0-63 points, where higher score indicates a healthier diet. The median (IQR) screener and HEI-2015 scores were 14.96 (11.99-18.36) and 48.96 (39.51-59.48), respectively. The simulated PHD score was highly correlated with the HEI-2015 score (Spearman rho 0.75) in NHANES 2017-18 and confirmed in NHANES 2015-16 data (Spearman rho 0.75).ConclusionsThe Penn Healthy Diet screener may be a useful tool for assessing diet quality due to its acceptable content validity, ease of administration, and ability to distinguish between servings of key food groups associated with a healthy versus unhealthy diet according to the HEI-2015. Additional research is needed to further establish the instrument's validity, and to refine a scoring algorithm.
| S-EPMC9670424 | biostudies-literature
Project description:The present work aimed to analyze, through the GlutenFreeDiet digital platform, the evolution over one year of the nutritional status, dietary profile and symptoms present among celiac people on a gluten-free diet (GFD) while receiving individualized dietary advice. Twenty-seven adults and thirty-one celiac children/adolescents participated in the study. This was then followed up by three visits, at diagnosis, and after 3 and 12 months (vt0, vt3 and vt12). Participants filled out dietary and gastrointestinal symptoms questionnaires. All patients received written personalized dietary advice from dietitians who interpreted data from the platform. Results obtained indicated that participants consumed proteins and lipids in excess and carbohydrates in defect. Low intakes of cereals, fruit and vegetables and high meat intakes were observed. However, gluten-free product (GFP) consumption and that of ultra-processed foods was reduced after 1 year in adults. Symptoms decreased after vt3 but recurred in vt12. Changes in ultra-processed foods and GFP intake, but lack of changes in the rest of the parameters suggested that the platform support was not effective enough. Even though the platform represents a useful tool for monitoring celiac patients and giving dietary advice, modules that require more continuous attention and nutritional education of patients should be provided for interventions to be more effective.
| S-EPMC8838721 | biostudies-literature
Project description:Healthy nutrition is widely considered the cornerstone of optimal athletic performance, both physically and mentally. This study investigates the critical role of healthy nutrition in shaping the physical and mental performance of athletes, with a specific focus on taekwondo. This research aims to explore the potential relationship between taekwondo athletes' attitudes towards healthy nutrition and their mental toughness. The research group comprised 276 active and licensed taekwondo athletes who voluntarily participated in the study (Age M = 17.18 ± SD = 7.13, N = 125 women, N = 151 men). Ethical approval for the research was obtained prior to the commencement of the study. Data collection instruments included the Healthy Nutrition Attitude Scale, Mental Toughness Scale, and a personal information form. Confirmatory factor analysis was conducted to confirm the validity and reliability of the scales. Descriptive statistics, correlation analysis, and regression analysis were performed to explore the relationship between the variables within the research model. The correlation analysis identified two significant, positive, and moderate correlations: (1) between knowledge about nutrition and mental toughness (r = 0.626) and (2) between positive nutrition and mental toughness (r = 0.672). The regression analysis revealed that both knowledge about nutrition (β = 0.360) and positive nutrition (β = 0.461) significantly contribute to mental toughness. The findings suggest that as athletes' knowledge of nutrition expands and their attitudes towards healthy eating become more positive, their mental toughness also appears to improve. These results are both important and original, adding significant new insights to the existing research landscape.
| S-EPMC10984172 | biostudies-literature
Project description:ObjectiveMany dietary assessment methods attempt to estimate total food and nutrient intake. If the intention is simply to determine whether participants achieve dietary recommendations, this leads to much redundant data. We used data mining techniques to explore the number of foods that intake information was required on to accurately predict achievement, or not, of key dietary recommendations.DesignWe built decision trees for achievement of recommendations for fruit and vegetables, sodium, fat, saturated fat and free sugars using data from a national dietary surveillance data set. Decision trees describe complex relationships between potential predictor variables (age, sex and all foods listed in the database) and outcome variables (achievement of each of the recommendations).SettingUK National Diet and Nutrition Survey (NDNS, 2008-12).SubjectsThe analysis included 4156 individuals.ResultsInformation on consumption of 113 out of 3911 (3 %) foods, plus age and sex was required to accurately categorize individuals according to all five recommendations. The best trade-off between decision tree accuracy and number of foods included occurred at between eleven (for fruit and vegetables) and thirty-two (for fat, plus age) foods, achieving an accuracy of 72 % (for fat) to 83 % (for fruit and vegetables), with similar values for sensitivity and specificity.ConclusionsUsing information on intake of 113 foods, it is possible to predict with 72-83 % accuracy whether individuals achieve key dietary recommendations. Substantial further research is required to make use of these findings for dietary assessment.
| S-EPMC4873899 | biostudies-literature
Project description:IntroductionMaintaining an affordable and nutritious diet can be challenging, especially for those living under the conditions of poverty. To fulfill a healthy diet, consumers must make difficult decisions within a complicated food landscape. Decisions must factor information on health and budget constraints, the food supply and pricing options at local grocery stores, and nutrition and portion guidelines provided by government services. Information to support food choice decisions is often inconsistent and challenging to find, making it difficult for consumers to make informed, optimal decisions. This is especially true for low-income and Supplemental Nutrition Assistance Program (SNAP) households which have additional time and cost constraints that impact their food purchases and ultimately leave them more susceptible to malnutrition and obesity. The goal of this paper is to demonstrate how the integration of data from local grocery stores and federal government databases can be used to assist specific communities in meeting their unique health and budget challenges.MethodsWe discuss many of the challenges of integrating multiple data sources, such as inconsistent data availability and misleading nutrition labels. We conduct a case study using linear programming to identify a healthy meal plan that stays within a limited SNAP budget and also adheres to the Dietary Guidelines for Americans. Finally, we explore the main drivers of cost of local food products with emphasis on the nutrients determined by the USDA as areas of focus: added sugars, saturated fat, and sodium.Results and discussionOur case study results suggest that such an optimization model can be used to facilitate food purchasing decisions within a given community. By focusing on the community level, our results will inform future work navigating the complex networks of food information to build global recommendation systems.
| S-EPMC10661405 | biostudies-literature