Food Recommendations Research Articles

WITHDRAWN: IOT enabled food recommender with NIR system

Abstract Food recommender system play an important role in the development of automatic systems for healthy living. Most of the work done in food recommendation systems focused on users choice, health status, Diets, nutrition consumption and the status of the food, the availability of the raw food is often overlooked. In the proposed work the system first check the raw food available inside the refrigerator and suggests user with various recipes based on the available raw food. The system consists of sensors to measure the quantity as well as quality of the raw food items, Computational unit, IoT Gateway and cloud for data storage and transmission. Results shows that the developed system suggests recipes to the user with the available raw food items correctly and also if there is any rottenness in the food items that too were identified correctly and ensured the retention of healthy and hygienic food items.

Design And Build Up Of Sphygmomanometer Based On Android Supplemented With Food Recommendations

Blood pressure is a measure of how strong the heart is to pump blood around the body. Abnormal blood pressure can occur due to high blood pressure (hypertension) or low blood pressure (hypotension). Data from the World Health Organization (WHO) in 2015 showed that around 1.13 billion people in the world have hypertension, meaning that 1 in 3 people in the world are diagnosed with hypertension. Therefore, a sphygmomanometer was designed that could digitally detect blood pressure and provide food recommendations to stabilize blood pressure. The detection of blood pressure is carried out by the oscillometry method where the oscillation value occurs when blood first flows into the artery after clogging. Systolic blood pressure is determined by multiplying the Mean Arterial Pressure by 0.8. Meanwhile, diastolic blood pressure is determined by multiplying the Mean Arterial Pressure by 0.5. The results of the blood pressure will be displayed on the LCD display and sent to the smartphone. On the smartphone, blood pressure results and food recommendations will be displayed through the android application to make it easier for patients to remember recommended foods and monitor their own blood pressure results without the help of a medical or doctor.

Adding Enriched Eggs in Ready-to-use foods Improve Recovery Rate in Malnourished Rats

Ready-to-use foods (RUFs) using indigenous sources in developing countries is highly required to treat moderate acute malnutrition (MAM). However, incorporating an animal protein may affect their effectiveness. Thus, two local RUFs were produced without (LF-1) and with eggs (LF-2). The objective of this study was to assess and compare to Plumpy'Sup (PS), the impact of adding enriched eggs in cashew/soy/rice based RUF on the proximate composition, growth and blood biochemical parameters in malnourished Wistar rats by Anagobaka diet. Proximate composition revealed that, with the exception of fiber and ash contents, the two RUFs recorded protein, lipid, carbohydrate and energy values globally comparable to PS. They also met WFP's recommendations for foods to treat MAM. Results of growth parameters show that Anagobaka diet leads to the installation of a moderate emaciation, confirmed by an average weight loss of -17 %. Moreover, recovery diets showed higher weight gain and good palatability (DMI, TPI, FER and PER) in rats fed with PS followed by those fed with LF-2 and LF-1. For the serum biochemical parameters, the rats fed with LF-2 had on the whole a better functioning of blood metabolites (glucose, total proteins, albumin, urea, creatinine, ASAT, ALAT) as well as a better accumulation of blood lipids (total cholesterol, HDL-cholesterol, LDL-cholesterol and triglycerides) than those of rats fed with PS and LF-1. In conclusion, local RUFs which include enriched eggs present the best nutritional profile to treat MAM in Côte d'Ivoire but to sustain recovery a mineral supplementation will be needed.

Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities

Background. Since physical activity has a high impact on patients with type 1 diabetes and the risk of hypoglycemia (low blood glucose levels) is significantly higher during and after physical activities, an automatic method to provide a personalized recommendation is needed to improve the blood glucose management and harness the benefits of physical activities. This paper aims to reduce the risk of hypoglycemia and hyperglycemia (high blood glucose levels), and empowers type 1 diabetes patients to make decisions regarding food choices connected with physical activities. Methods. Traditional and Bayesian feedforward neural network models are developed to provide accurate predictions of the blood glucose outcome and the risks of hyperglycemia and hypoglycemia with uncertainty information. Using the proposed models, safe actions that minimize the risk of both hypoglycemia and hyperglycemia are provided as food recommendations to the patient. Results. The predicted blood glucose responses to the optimal and safe food recommendations are significantly better and safer than by taking random food. Conclusions. Simulations conducted on the state-of-the-art UVA/Padova simulator combined with Brenton’s physical activity model show that the proposed methodology is safe and effective in managing blood glucose during and after physical activities.

The role of cultural beliefs on eating patterns and food practices among pregnant women: a systematic review.

Despite the importance of cultural beliefs in clinical practice, few systematic reviews have investigated how these beliefs influence food practices in pregnant women. To explore the role of cultural beliefs in eating patterns and food practices among pregnant women, highlighting food recommendations, food taboos and restrictions, and their association with health. A systematic review was conducted using the following electronic databases: PubMed, Scopus, CINAHL, PsycINFO, and Web of Science from May 2014 to May 2019. Articles were included if the studies included pregnant women, analyzed how cultural beliefs may influence eating patterns, were peer-reviewed articles with original data, published in the last 5 years, and in English or Spanish language. Quality assessment was also performed. A total of 544 articles were identified in the search and 24 were included in the final analysis (17 using qualitative design, 6 using quantitative design, and 1 with a mixed-design). These studies were predominantly from the African continent (n = 15). Our findings showed that culture is a key factor related to "taboos" and food restrictions, which are transmitted by the family or members of community, having a strong religious or spiritual influence. All these restrictions are related to the fear of unfavorable pregnancy outcomes such as the risk of abortion, dystocia, and congenital macrosomia, or are used to avoid child problems such as cutaneous and respiratory disorders. Findings from this study indicate cultural beliefs are strongly associated with food patterns and eating habits in pregnant women. Administrators and health professionals should be aware of these beliefs to minimize problems in the perinatal period.

Parental Food Beliefs on Pre-School-Aged Children in Kaski District of Nepal: A Qualitative Review

Background: This study explores food beliefs among poor mothers related to feeding their offspring. Mothers’ misconception of a healthy diet is one of the major causes of nutritional problems in preschool-aged children in Nepal and these beliefs and attitudes can result in the inappropriate feeding of young children. Objectives: The main objectives of this study were: • identify major barriers for recommending healthy food that are associated with existing cultures, religions and ethnic divisions; • assess the knowledge, attitudes, and beliefs about nutritious food amongst mothers; • assess health-seeking behaviour for children of low socio-economic status. Methods: Study used a qualitative focus group discussion. Fifty participants took part in seven focus groups to explore their food beliefs. The qualitative focus groups aimed to collect in-depth information around food beliefs and data were thematically analysed. Results: The study identified six key themes: (a) poverty; (b) knowledge; (c) policy; (d) beliefs about breastfeeding; (e) food beliefs: and (f) health-seeking behaviours/cultural influences. Many participants thought that illiterate and underserved populations are generally exposed due to financial scarcity, poor knowledge and strongly rooted in cultural practices, and beliefs. This study found ‘diversified views’ as a major barrier to food and health-seeking behaviours. Some groups recognised the negative effects of existing beliefs and taboos. However, the spiritual healers highlighted the importance of linking beliefs with cultural and religious norms and values. They showed the complex relationships between food and health-seeking behaviours and food recommendations with financial status and the perceived cultural practices of society. Conclusions: This study suggests that a public health approach is needed to address nutrition problems associated with behaviour and revealed major barriers which were associated with poverty, resources, and mothers’ education level.

Healthy diet recommendation via Food‐Nutrition‐Recipe Graph mining

AbstractGood nutrition and balance dietary pattern play vital roles of leading a healthy lifestyle. Prior studies showed that the healthy diet can successfully reduce the risk of chronic diseases (e.g., type 2 diabetes and cancer) and bring other well‐documented benefits. Existing food recommendation models, however, often solely rely on user's feedback (e.g., click and purchase data), which aims to optimize Click‐Through Rate (CTR) but ignores the importance of health needs of users. Intuitively, a healthy diet recommendation requires a comprehensive consideration of different kinds of information, such as nutrition, ingredients and cooking methods. In this study, by collecting the data from FoodData Central (FDC), recipe websites, and scientific literature, we construct a heterogeneous graph, Food‐Nutrition‐Recipe Graph (FNRG), by integrating information of nutrition, food (ingredients), and recipes. A random walk based graph mining approach is proposed to meet the health needs of users. Experiments results show that the proposed method can successfully address the health information needs for people who suffer from chronic diabetes.

Energy and Nutrient Intake of Americans according to Meeting Current Dairy Recommendations

Most Americans do not meet dairy food recommendations from the 2015 Dietary Guidelines for Americans (DGA). This study assesses differences in nutrient intake between Americans who meet recommendations for dairy intake and those who do not, using data from the National Health and Nutrition Examination Survey from 2013–2014 and 2015–2016 (n = 5670 children ages 2–18 years and n = 10,112 adults ages 19+). Among children and adults, those meeting dairy food recommendations were significantly more likely to have adequate intake (% above Estimated Average Requirement (EAR)) of calcium, magnesium, phosphorus, riboflavin, vitamin A, vitamin B12, and zinc and consume above the Adequate Intake (AI) for potassium and choline than Americans not meeting dairy recommendations, regardless of age, sex, or race/ethnicity. Americans meeting dairy recommendations were also more likely to exceed recommendations for sodium and saturated fat but consume less added sugars. Nearly 60% of Americans 2 years and older not meeting dairy recommendations consumed calcium and magnesium below the EAR. Only about 20% of Americans who did not meet dairy recommendations consumed above the AI for potassium. Dairy foods make important and unique contributions to dietary patterns, and it can be difficult to meet nutrient needs without consuming recommended amounts of dairy foods.

MALNUTRITION-CHALLENGE IN 21ST CENTURY AND PROBABLE CONTRIBUTION OF AYURVEDA THROUGH MORINGA LEAVES

Nutritive diet has grabbed the center stage in current times among common men as well as researchers &food has turned into a whole damn industry. Despite of everything, Malnutrition is the largest single contributor to diseases in the world & leads to 45% of all deaths in children under 5 in developing countries. Due to interrelated mother- child nutrition, if a breastfeeding mother gets required nutrition, her kid becomes healthy. The causes of improper nutrition are variable but lack of nutritious food combinations in all classes are most important throughout the world.
 Ayurveda is science of individualistic need based dietetics & nutrition and describes foods accordingly. There is recommendation of a super food named Shigru (Moringa) for Sutika (lactating mothers) in Bheshajyaratnawali,taking this as reference we have conceptualized a food combination of Moringa +wheat flour+ jaggery which is super nutritious and serves as a cheap, affordable, easy to collect and easy to make, palatable preparation.
 When 11% of the world’s population is under nourished, need for such right food combination increases manifolds. Owing to per 100g nutritive value of these contents and their cost effectiveness, this combination has a potential to be a perfect staple dietary option for nutrition deficit individuals. It needs to be further established at large scale through RCTs so that large population can be benefitted.

A dog food recommendation system based on nutrient suitability

AbstractThe demand for a food recommendation service for dogs has rapidly increased with the increasing number of pet owners, because it is generally difficult for dog owners to find food that is perfectly suitable for their dogs' health condition. The purpose of this study is to develop an algorithm for recommending dog food that contains appropriate nutrients based on the physical and health conditions of the dogs. This study proposes a nutrient profiling‐based recommendation algorithm (NRA) for dog food. The proposed algorithm tries to recommend appropriate or inappropriate dog food by using collective intelligence based on user experience and the prior knowledge of experts. Based on the physical and health status of dogs, this study extracts which nutrients are necessary for the dogs and recommends the most suitable dog food containing these nutrients. A performance evaluation was implemented in terms of recall, precision, F1 and AUC. As a result of the performance evaluation, the AUC performance of this NRA is 20% higher than k‐NN and 9.7% higher than the SVD model. In addition, the NRA proved to be an evolving system in which the performance of recommendations improves as users' feedback accumulates.

Assessing Diet Quality in a Racially and Ethnically Diverse Cohort of Low-income Toddlers.

Low-income racially and ethnically diverse children are at higher risk for obesity compared with their counterparts; yet, few studies have assessed their diet quality. The aim of the study was to evaluate the diet quality of a racially and ethnically diverse cohort of 2-year-olds using the Healthy Eating Index (HEI)-2010. We used 24-hour dietary recall data from caregivers of toddlers (24-34 months) at 4 pediatric resident clinics that participated in the Greenlight Study to calculate compliance with the Dietary Guidelines for Americans (DGA) using total HEI score (range 0-100) and 12 component scores. Participants (n = 231) were mostly Hispanic (57%) or non-Hispanic black (27%) and from low-income families. Mean HEI-2010 score was 62.8 (standard deviation [SD] 10.5). Though not significant, Hispanics had the highest HEI score. Toddlers of caregivers without obesity, older than 35 years and born outside the United States had higher HEI scores. Most had high HEI component scores for dairy, fruit, and protein foods, but few achieved maximum scores, particularly for whole grains (13%), vegetables (10%), and fatty acid ratio (7%). Despite scores reflective of DGA recommendations for fruit, dairy and protein foods, toddlers in this diverse sample had low quality diets as measured by the HEI, driven largely by low component scores for whole grains, vegetables, and ratio of unsaturated to saturated fatty acids.

Understanding user Taste Preferences for Food Recommendation

Understanding user Taste Preferences for Food Recommendation - written by A. Naresh , B. Purushottam Yadav , M. S. S. Shaastry published on 2020/06/05 download full article with reference data and citations

Comparing Diet Quality of School Meals versus Food Brought from Home.

Purpose: Consuming nutritious food is essential to learning. The purpose of this research was to determine the diet quality of elementary school lunches, both those in meal programs and those bringing food from home, in urban and rural locations in Saskatchewan.Methods: Using a School Food Checklist and digital photography we compared food group servings and diet quality in 3 school types: urban schools with a meal program and urban and rural schools without a meal program. The total sample was 773 students.Results: Only 55% of students brought the minimum number of servings for grain products and meat and alternatives, with fewer bringing the minimum for vegetables and fruit (25.6%-34.9%), whole grains (24.1%), and milk and alternatives (14.1%). Students bringing food from home had significantly more calories in their lunches from minimally nutritious foods. Students in meal programs had the highest diet quality scores using the Healthy Eating Index adapted for school hours.Conclusions: The diet quality of elementary students' lunches needs improvement, although students in meal programs have healthier diets. Interventions targeting what children eat at school should focus on increasing the number of students meeting recommendations for healthy foods while decreasing minimally nutritious foods brought to school.

Usual Intake of Food Components in Adults Age 71+ from WWEIA, NHANES 2013–2016

Abstract Objectives Compare the usual intake of food components and the percent meeting the Dietary Guidelines for Americans 2015–2020 (DGA) energy-specific recommendations for males and females age 71+. Methods This analysis is based on 24-hr recalls from 1422 individuals age 71 and older from What We Eat in America, National Health and Nutrition Examination Survey 2013–2016 (WWEIA, NHANES). It uses the Food Patterns Equivalents Databases for 2013–2014 and 2015–2016. These databases contain the amounts of Food Patterns components for each food and beverage reported by each WWEIA, NHANES respondent. Usual intake distributions of selected food patterns components are estimated using the National Cancer Institute method. These distributions are then compared to the energy-specific recommendations in the DGA as appropriate for each respondent, based on age, sex, and physical activity level. The NHANES Physical Activity Questionnaire is used to classify respondents as sedentary, moderately active, or active. Results Significantly more males than females meet the energy-specific recommendation for protein foods (52% vs 30%, P < .001) and dairy foods (6% vs 1%, P < .001) while significantly more females than males meet the recommendation for limiting sodium (34% vs 9%, P < .001). There are no significant differences between males and females meeting the recommendations for vegetables, fruits, grains, added sugars, and saturated fat. Within the protein foods subgroups, significantly more males than females meet the recommendations for the meat, poultry, and egg subgroup (59% vs 40%, P < .001), but there are no differences for the total fish and seafood or the nuts, seeds, and soy products subgroups. Within the vegetable subgroups, there are no significant differences between males and females meeting the recommendations for dark green, red/orange, total starchy, legumes or other vegetables. Conclusions Less than half of adults age 71+ meet any of the DGA energy-specific recommendations with the exception of males where 52% meet the recommendation for protein foods and 59% meet the recommendation for the meat, poultry, egg subgroup within protein foods. Only 1% of women meet the recommendation for dairy foods. Funding Sources USDA, ARS.

Recomendaciones medioambientales, alimentarias y nutricionales para el manejo del niño asmático en edad escolar

Objetivo: elaborar recomendaciones para el control del asma en edad escolar. Metodología: investigación cualitativa realizada en el período 2013-2015. Se realizó una revisión bibliográfica y documental. Se confeccionó una guía para lo cual se utilizó la metodología propuesta por Moriyama. Se consultó un grupo de expertos integrado por cinco investigadores, formados en diferentes ramas del saber y que han transitado por diferentes niveles del sistema de salud. Resultados: las recomendaciones alimentarias, nutricionales y del ambiente en el hogar para niñas y niños asmáticos están estructuradas en dos partes, una de información sobre alimentación y nutrición y otra sobre medidas de control ambiental. Limitaciones: la contextualización de las recomendaciones para el manejo alimentario, nutricional y medioambiental incluidas en la estrategia. Conclusiones: sobre la base de los factores de riesgo y protectores, se propusieron recomendaciones para el manejo alimentario, nutricional y del ambiente en el hogar como estrategia para el control del asma, dirigidas a profesionales de la salud, pacientes y familiares.

Dietary interventions for multiple sclerosis-related outcomes.

Dietary interventions for multiple sclerosis-related outcomes.

What-To-Taste: A Food Recommendation System

The Food recommendation system software is relatively new in this era, with the recommendation system that focuses on the user preferences posited. Generally we get confused about what to eat or try next, this problem is solved by our project, which recommends food according to customer’s experience, customer’s ratings on cuisine and customer’s taste. “What-To-Taste” is a food recommendation system which can be used by the food chain industry to keep recommending their customers about the cuisine, basically whatever they have in their menu, based on their customer tastes, interests and order history. Each human has a different taste that can be verified from recommendation data at every new place and the best cuisine served is location-dependent by rating through the customer. The Food recommendation system recommends by Food profiling, User profiling, and recommending the specific food item as per the last feedback submitted by the users.

Vector copy number quality control testing for CAR T-cells: critical validation parameters

Background & Aim Background Retroviral and lentiviral vectors have been broadly used in Chimeric Antigen Receptor (CAR) T-cell therapy clinical trials. These vectors have the capacity to integrate permanently into host cell DNA. There is an increased risk of oncogenesis if the vector copy number (VCN) per cell is high. The Food and Drug Administration (FDA) recommends that the VCN shall be Aims Establish a reliable test for detection of VCN in patient samples. Evaluate the linearity of the vector copy number qPCR and primer multiplexing. Methods, Results & Conclusion Methods CD3+ T-cells from three individuals with no tumour burden were transduced using a retroviral vector to generate CAR T-cells. CAR T-cells and the Un-transduced T-cells (controls) were expanded in the same culturing conditions for 14 days. Genomic DNA was extracted from the six samples using Qiagen DNA extraction kit. Human albumin (huALB) and the retroviral vector backbone copy numbers were detected using qPCR with TaqMan probes against a standard curve. Results The Vector Copy Number of the CAR-T cell products were 5, 3, and 2 copies for Donor 1, 2 and 3, respectively. Multiplexing of huALB and vector probes did not impact the accuracy of VCN detection. The linear correlation coefficient was r2 = 0.992 ± 0.003. Conclusion qPCR is a sensitive and reliable quality control test for detection of VCN in CAR T-cells. A number of critical process parameters and key variables need to be considered when preparing VCN validation protocols.

WHAT-TO-TASTE: A FOOD RECOMMENDATION SYSTEM

The Food recommendation system software is relatively new in this era, with the recommendation system that focuses on the user preferences posited. Generally we get confused about what to eat or try next, this problem is solved by our project, which recommends food according to customer’s experience, customer’s ratings on cuisine and customer’s taste. “What-To-Taste” is a food recommendation system which can be used by the food chain industry to keep recommending their customers about the cuisine, basically whatever they have in their menu, based on their customer tastes, interests and order history. Each human has a different taste that can be verified from recommendation data at every new place and the best cuisine served is location-dependent by rating through the customer. The Food recommendation system recommends by Food profiling, User profiling, and recommending the specific food item as per the last feedback submitted by the users.

Trans fatty acid intake among Chinese population: a longitudinal study from 1991 to 2011

ObjectiveThis study was aimed to roughly describe individual Trans Fatty Acids (TFAs) intake and the percentage of energy intake(E%), and identify major food sources in the Chinese population, taking gender, age, and regional distribution into the consideration, as well as examining temporal changes over the course of 20 years.MethodThis multi-center study, covering nine provinces among populations aged ≥ 3 in China, was conducted to collect food consumption information from 1991 to 2011. A classical assessment method was used to estimate the level of dietary TFA intake.ResultsOver the 20-year period, the intake of TFAs in Chinese populations had increased, but remained at a relatively lower level (from 0.25 g/d(0.11% for E%) to 0.53 g/d(0.24% for E%)) compared with that of other countries and the World Health Organization (WHO) recommended level. Collectively, males and participants aged 19–60 generally consumed more TFA-containing foods. People in eastern regions consumed more TFAs and had a higher E% than those in western area. Industrial sources of TFAs, especially vegetable oil, ranked as the principal food sources of TFAs in the Chinese population. Natural sources of TFAs have gradually increased in proportion among children and adolescents.ConclusionsTFA intake and the E% are commonly under the recommended level in the general population in China. Presently, restriction of vegetable oil could be a crucial method to reduce TFA intake. It would be critical to facilitate and promote public health that food recommendations might be based on the dietary preferences for population separated by different ages and regions.