Mining of nutritional ingredients in food for disease analysis

Suitable nutritional diets have been widely recognized as important measures to prevent and control non-communicable diseases (NCDs). However, there is little research on nutritional ingredients in food now, which are beneficial to the rehabilitation of NCDs. In this paper, we profoundly analyzed the relationship between nutritional ingredients and diseases by using data mining methods. First, more than 7,000 diseases were obtained and we collected the recommended food and taboo food for each disease. Then, referring to the China Food Nutrition, we used noise-intensity and information entropy to find out which nutritional ingredients can exert positive effects on diseases. Finally, we proposed an improved algorithm named CVNDA_Red based on rough sets to select the corresponding core ingredients from the positive nutritional ingredients. To the best of our knowledge, this is the first study to discuss the relationship between nutritional ingredients in food and diseases through data mining based on rough set theory in China. The experiments on real-life data show that our method based on data mining improves the performance compared with the traditional statistical approach, with the precision of 1.682. Additionally, for some common diseases such as Diabetes, Hypertension and Heart disease, our work is able to identify correctly the first two or three nutritional ingredients in food that can benefit the rehabilitation of those diseases. These experimental results demonstrate the effectiveness of applying data mining in selecting of nutritional ingredients in food for disease analysis

Discussion documents – SUSVAR Visions Workshop, Karrebæksminde, Denmark, April 2008

Seven discussion documents were made during the SUSVAR Visions workshop ‘Sustainable cereal production beyond 2020: Visions from the SUSVAR1 network’, Karrebæksminde, Denmark, 14-16 April 2008. At the workshop, one discussion documents was written for each of the topics mentioned below. In total 55 persons from 21 European countries participated in the process. The participants came from different disciplines: genetics, plant breeding, genetic resources, agronomy, plant pathology, soil science, biometry and system analysis, all specialised in the area of cereal production. The approach taken at the workshop was to focus on envisioning the future of sustainable agriculture, especially cereal production. This was done by scientific creative thinking on the basis of possibilities in breeding, management and seed production and not on the basis of traditional problem solving. We followed a strategy commonly used in industrial management based on the premise “imagining the future is shaping the future”. The method “appreciative inquiry” was applied supported by a professional facilitator. Experience shows that this way of working sparks engagement and creativity and that progress and results can be reached within a short time. Focus was on the following topics of relevance to cereal production: - Competition between food and bioenergy, - Soil fertility management, - Economical and legal conditions for variety improvement, - Participation of stakeholders, - Plant breeding strategies, - Food and feed processing improvements, - Sustainable land use. The initial process was to visualise the most desirable future scenario for the seven essential topics in food and agriculture systems. This process was unhindered by no requirement for a market-driven goal. Each topic was discussed in relation to a broader socio-ecological system with a focus on the means to reach the desired and more sustainable outcomes. The next step at the workshop was to produce the discussion documents. The final stage of the process is to connect the topics in a completed vision of cereal production within a future sustainable socio-ecological system. This is in progress by a group of key persons within the network, e.g. the working group leaders (in preparation for publication in a scientific journal)

Exploring the Readability of Ingredients Lists of Food Labels with Existing Metrics

Healthy diet and dietary behaviors are key components in prevention of chronic disease and management of chronic illness. Nutritional literacy has been associated with dietary behaviors and consumer choice of healthy foods. Nutritional literacy can be measured, for example, by examining consumer food label use, but current research focuses largely on the Nutrition Facts panel of a food product. Ingredients lists are critical for communicating food composition but are relatively unstudied in existing literature. The goal of this work is to measure the readability of ingredients lists on branded food products in the United States using existing metrics. We examined ingredients lists for all 495,646 products listed in the USDA Food Data Central database using four existing readability measures for text written in natural language. Each of these indices approximates the grade level that would be expected to comprehend a text; comparatively, patient consent forms are considered acceptable at an 8th grade reading level or lower. We report a broad variability for in readability using different metrics: ingredients lists recorded at a 9th grade reading level or higher to comprehend are found at rates of 16.5% (Automated Reading Index) to 74.9% (Gunning-Fog Index). Ingredients lists recorded at a 10th grade reading level or higher to comprehend are found at rates of 84.2% (using FRE Index). These results demonstrate the need to further explore how ingredients lists can be measured for readability, both for the purposes of consumer understanding as well as for supporting future nutrition research involving text mining

A Study about Discovery of Critical Food Consumption Patterns Linked with Lifestyle Diseases for Swiss Population using Data Mining Methods

Background: This article demonstrates that using data mining methods such as association analysis on an integrated Swiss database derived from a Swiss national dietary survey (menuCH) and Swiss demographical and health data is a powerful way to determine whether a specific population subgroup is at particular risk for developing a lifestyle disease based on its food consumption patterns. Objective: The objective of the study was to use an integrated database of dietary and health data from a large group of Swiss population to discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food con-sumption. Design: Food consumption databases from a Swiss national survey menuCH were gathered along with corresponding large survey of demographics and health data from Swiss population conducted by Swiss Federal Office of Public Health (FOPH). These databases were integrated and reported in a previous study as a single integrated database. A data mining method such as A-priori association analysis was applied to this integrated database. Results: Association mining analysis was used to incorporate rules about food consumption and lifestyle diseases. A set of promising preliminary rules and their corresponding interpretation was generated, which is reported in this paper. As an example, the found rules of the sample show that smoking is relatively irrelevant to the high blood pressure and Diabetes, whereas consuming vegetables at regular basis reduces the risk of high Cholesterol. Conclusions: Association rule mining was successfully used to describe and predict rules linking food consumption patterns with lifestyle diseases. The gained association rules reveal that the appearance of the mutually independent nutritional characteristics in the rules are equally distributed.Furthermore, most of the sample show no chronic diseases as they smoke little and exercise regularly, which can be interpreted that sport is a strong preventive factor for chronic/lifestyle diseases. Nevertheless, a small percentage of the sample shows chronic illnesses due to unhealthy eating. Further research should consider the weighting of chronic diseases’ characteristics for them not to be pruned out early by data mining computation

Nutritional and Phytochemical Content of High-Protein Crops

The authors acknowledge support from the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS) via their strategic research and partnership programs.Peer reviewedPostprin

Shared Value in Chile: Increasing Private Sector Competitiveness by Solving Social Problems

Over the last few decades, Chile has experienced rapid and sustained economic, social, and institutional development. Crucial challenges remain, however, in the form of social inequity, lack of opportunity, mistrust, and social unrest. The Chilean private sector is at an inflection point in its relationship with society. The corporate sector has both contributed to and benefited from the growth and development of the last decades, but remaining social challenges pose significant constraints to the continued growth of the private sector. High levels of mistrust regarding the role of business in society reflect a widespread belief that profit making activities are merely a demonstration of corporate greed. The Chilean private sector faces a frequently antagonistic relationship with government and civil society that will likely worsen unless companies are able to find ways to authentically link their businesses to efforts to solve Chile's social problems. On the other hand, if government and civil society conclude that the private sector has no contribution to make to the country's social and economic development strategy, Chile will squander an important engine for creating shared prosperity. The good news is that there does not need to be a trade-off between private sector competitiveness and greater prosperity for all Chileans. Shared value, a concept explained in Harvard Professor Michael Porter and Mark Kramer's Harvard Business Review articles, suggests an approach for companies to increase their competitiveness and profitability by helping to solve social problems. The public sector and civil society can increase the social benefits from shared value by thoughtfully partnering with the private secto