Search Results (8)

Background/Objectives: Improving one’s diet for the purpose of promoting health is constrained by people’s ingrained eating habits, as the eating patterns that align with their established habits do not necessarily correspond to a healthy way of eating. In addressing the issue of improving diet while taking both health and habits into consideration, this paper focuses on three concepts of complementarity related to food combinations and presents an approach using Japanese data. Methods: This paper first organizes three concepts of complementarity related to food combinations. The three concepts of complementarity are formulated based on (i) nutrients, (ii) habits, and (iii) recipes. The definitions of measurement scales corresponding to these concepts are also discussed. Results: Using data from a specific region in Japan, we analyzed three types of complementarities related to food combinations across different gender and age groups. This approach enabled us to visualize the potential for dietary improvements and identify effective strategies tailored to each group. For instance, among females aged 50 and above in this region, it was found that recipes incorporating combinations such as (α) milk and pasta, (β) salmon and pasta, (γ) horse mackerel or sardines with carrots, and (δ) onions with taro can efficiently support dietary improvement for this demographic, building upon their established dietary habits. The differences in recommended recipes for each group are due to variations in nutrients that tend to be insufficient and differences in established eating habits. Conclusions: A combination of foods with high (i) complementarity of nutrients constitutes a healthy diet, whereas a combination of foods with low (ii) complementarity in habits reflects dietary behaviors that are not sufficiently practiced within the relevant sub-population at present. Meanwhile, combinations of foods with high (iii) complementarity in recipes can serve as tools to bridge the gap between healthy eating patterns and established dietary habits. Full article

In addressing the challenge of assessing healthy brain aging across diverse interventions, this study introduces the use of MRI-derived Brain Healthcare Quotients (BHQ) for comprehensive evaluation. We analyzed BHQ changes in 319 participants aged 24–69, who were allocated into dietary (collagen peptide, euglena, matcha, isohumulone, xanthophyll) and physical activity (hand massage with lavender oil, handwriting, office stretching, pink lens, clinical art) groups, alongside a control group, over a month. These interventions were specifically chosen to test the efficacy of varying health strategies on brain health, measured through BHQ indices: GM-BHQ for gray matter volume, and FA-BHQ for white matter integrity. Notably, significant improvements in FA-BHQ were observed in the collagen peptide group, with marginal increases in the hand massage and office stretching groups. These findings highlight BHQ’s potential as a sensitive tool for detecting brain health changes, offering evidence that low-intensity, easily implemented interventions can have beneficial effects on brain health. Moreover, BHQ allows for the systematic evaluation of such interventions using standard statistical approaches, suggesting its value in future brain healthcare research. Full article

Background and Objectives: Diet is an important modifiable cancer risk factor. Studies show that adherence to dietary guidelines reduces cancer risk and that adherence is affected by the complexity of dietary actions and the awareness of their effect. Intervention on complex nutrition issues requires clear nutrition messages to the public. To improve adherence for cancer prevention purposes, this research describes a method to provide tailored dietary recommendations by prioritizing dietary advice from the guideline, based on diet–disease relationships revealed by disease risk models. In addition, we developed the method as a risk calculator framework to provide the interoperability between risk models and guidelines. The framework is integrated into our cancer prevention app to facilitate risk communication and guideline adherence. Methods: We propose a simple and intuitive method to define and align cancer risk models and dietary guidelines using object-oriented programming paradigms, which can encapsulate the relationship between dietary advice, cancer risk, and lifestyle variables. The effect of each action can be simulated by applying modified dietary variables into the probability model to calculate an expected risk change. An interactive intervention is then designed to enhance understanding and promote the adoption of dietary actions. It consists of three steps: selecting dietary actions ranked by their preventive effect on cancer risk, modifying selected variables to desired values, and visualizing the simulated changes in cancer risk with dietary actions by humanoid pictogram. Results: We demonstrate the mapping of actions to the corresponding variables for a chosen cancer risk prediction model while ranking them according to their preventive effect. We further show that our method can easily be adapted to any dietary guideline. We implemented more than 10 cancer risk models covering common cancer types and integrated them into the system. Moreover, it is simple to add other cancer risk models to support the prevention of additional cancer types. As a key feature of a web-based application, the practical use of the method allows for the delivery of personalized action suggestions and notifications based on the user’s lifestyle factors. An usability testing was carried out between August and October 2023 with 9 participants using the guideline made by German Nutrition Society (DGE). The test proved the intervention’s effectiveness. Discussion: On the frontier of nutrition science and preventive medicine, our work is the first approach that combines risk models and dietary guidelines into a comprehensive digital health intervention system. It informs the user about the most impactful dietary behaviors, promotes adherence to dietary guidelines, and, accordingly, facilitates cancer risk reduction. Full article

Dietary assessments hold significant importance within the field of public health. However, the current methods employed for dietary assessments face certain limitations and challenges that necessitate improvement. The aim of our study was to develop a reliable and practical dietary assessment tool known as photo-assisted dietary intake assessment (PAD). In order to evaluate its validity, we conducted an analysis on a sample of 71 college students’ dinners at a buffet in a canteen. We compared estimates of food weights obtained through the 24-h recall (24 HR) or PAD method with those obtained through the weighing method; we also evaluated the feasibility of PAD for recording dinner intakes among a sample of college students (n = 76) and elderly individuals (n = 121). In addition, we successfully identified the dietary factors that have a significant impact on the bias observed in weight estimation. The findings of the study indicated that the PAD method exhibited a higher level of consistency with the weighing method compared to the 24 HR method. The discrepancy in D% values between cereals (14.28% vs. 40.59%, P < 0.05), vegetables (17.67% vs. 44.44%, P < 0.05), and meats (14.29% vs. 33.33%, P < 0.05) was clearly apparent. Moreover, a significant proportion of the food mass value acquired through the PAD method fell within the limits of agreement (LOAs), in closer proximity to the central horizontal line. Furthermore, vegetables, cereals, eggs, and meats, for which the primary importance lies in accuracy, exhibited a considerably higher bias with the 24 HR method compared to the PAD method (P < 0.05), implying that the PAD method has the potential to mitigate the quality bias associated with these food items in the 24 HR method. Additionally, the PAD method was well received and easily implemented by the college students and elderly individuals. In conclusion, the PAD method demonstrates a considerable level of accuracy and feasibility as a dietary assessment method that can be effectively employed across diverse populations. Full article

While there is some research investigating whole foods or diets that are easily understood and accessible to patients with osteoarthritis, specific nutrients or nutraceuticals are more commonly identified. Unfortunately, guidelines and evidence surrounding individual nutrients, extracts, and nutraceuticals are conflicting and are more difficult to interpret and implement for patients with osteoarthritis. The purpose of this umbrella review is to provide a comprehensive understanding of the existing evidence of whole foods and dietary patterns effects on osteoarthritis-related outcomes to inform evidence-based recommendations for healthcare professionals and identify areas where more research is warranted. A literature search identified relevant systematic reviews/meta-analyses using five databases from inception to May 2022. Five systematic reviews/meta-analyses were included in the current umbrella review. Most evidence supported the Mediterranean diet improving osteoarthritis-related outcomes (e.g., pain, stiffness, inflammation, biomarkers of cartilage degeneration). There was little to no evidence supporting the effects of fruits and herbs on osteoarthritis-related outcomes; however, there was some suggestion that specific foods could potentiate symptom improvement through antioxidative mechanisms. The overall lack of homogeneity between the studies limits the conclusions that can be made and highlights the need for quality research that can identify consumer-accessible foods to improve osteoarthritis-related symptoms. Full article

A number of studies in the general population showed that healthy dietary patterns, such as the Mediterranean Diet, can improve or prevent the development of several chronic diseases and are associated with a significant reduction in all-cause and cardiovascular mortality. The Mediterranean diet may also have favorable effects for the prevention of chronic kidney disease (CKD), but no evidence of renoprotection exists in CKD patients. The Mediterranean Renal (MedRen) diet is an adaptation of the Mediterranean diet recommendations comprising a quantitative reduction in the RDA values of protein, salt and phosphate intake for the general population. Hence, MedRen supplies 0.8 g/Kg of protein, 6 g of salt and less than 800 mg of phosphate daily. Obviously, there is a preference for products of plant origin, which contain more alkali, fibers, unsaturated fatty acids than animal-based food. The MedRen diet can be implemented easily in mild-to-moderate stages of CKD with good results, both in terms of adherence to prescriptions and metabolic compensation. In our opinion, it should be the first step of CKD stage 3 nutritional management. This paper describes the features and reports our experience in the implementation of the MedRen diet as an early nutritional approach to CKD. Full article

It is well known that many chronic diseases are associated with unhealthy diet. Although improving diet is critical, adopting a healthy diet is difficult despite its benefits being well understood. Technology is needed to allow an assessment of dietary intake accurately and easily in real-world settings so that effective intervention to manage being overweight, obesity, and related chronic diseases can be developed. In recent years, new wearable imaging and computational technologies have emerged. These technologies are capable of performing objective and passive dietary assessments with a much simplified procedure than traditional questionnaires. However, a critical task is required to estimate the portion size (in this case, the food volume) from a digital image. Currently, this task is very challenging because the volumetric information in the two-dimensional images is incomplete, and the estimation involves a great deal of imagination, beyond the capacity of the traditional image processing algorithms. In this work, we present a novel Artificial Intelligent (AI) system to mimic the thinking of dietitians who use a set of common objects as gauges (e.g., a teaspoon, a golf ball, a cup, and so on) to estimate the portion size. Specifically, our human-mimetic system “mentally” gauges the volume of food using a set of internal reference volumes that have been learned previously. At the output, our system produces a vector of probabilities of the food with respect to the internal reference volumes. The estimation is then completed by an “intelligent guess”, implemented by an inner product between the probability vector and the reference volume vector. Our experiments using both virtual and real food datasets have shown accurate volume estimation results. Full article

This study aimed at designing a—diet high in slowly digestible starch (SDS) by carefully selecting high-SDS starchy products and to validate its implementation, acceptance, and impact on the postprandial glycemic response in patients with type 2 diabetes (T2D). Starchy products were screened and classified as being either high (high-SDS) or low (low-SDS) in SDS (in vitro SDS method). A randomized controlled cross-over pilot study was performed: Eight patients with T2D consumed randomly a high-SDS or a low-SDS diet for one week each, while their glycemic profile was monitored for 6 days. Based on 250 food product SDS analyses and dietary recommendations for patients with T2D, the high-SDS and low-SDS diets were designed. The high-SDS diet significantly increased SDS intake and the SDS/carbohydrates proportion compared to the low-SDS diet (61.6 vs. 11.6 g/day and 30% vs. 6%; p < 0.0001, respectively). Increasing the SDS/carbohydrate proportion to 50% of the meal was significantly correlated with a 12% decrease in tAUC0–120 min and a 14% decrease in the glycemic peak value (p < 0.001 for both). A high-SDS diet can be easily designed by carefully selecting commercial starchy products and providing relevant recommendations for T2D to improve their glycemic profile. Full article