搜索结果：Food research international (Ottawa, Ont.)

Obesity is a complex, chronic, stigmatized disease whereby abnormal or excess body fat may impair health or increase the risk of medical complications, and can reduce quality of life and shorten lifespan in children and families. We developed this guideline to provide evidence-based recommendations on options for managing pediatric obesity that support shared decision-making among children living with obesity, their families, and their health care providers. We followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. We used the Guidelines International Network principles to manage competing interests. Caregivers, health care providers, and people living with obesity participated throughout the guideline development process, which optimized relevance. We surveyed end users (caregivers, health care providers) to prioritize health outcomes, completed 3 scoping reviews (2 on minimal important difference estimates; 1 on clinical assessment), performed 1 systematic review to characterize families' values and preferences, and conducted 3 systematic reviews and meta-analyses to examine the benefits and harms of behavioural and psychological, pharmacologic, and surgical interventions for managing obesity in children. Guideline panellists developed recommendations focused on an individualized approach to care by using the GRADE evidence-to-decision framework, incorporating values and preferences of children living with obesity and their caregivers. Our guideline includes 10 recommendations and 9 good practice statements for managing obesity in children. Managing pediatric obesity should be guided by a comprehensive child and family assessment based on our good practice statements. Behavioural and psychological interventions, particularly multicomponent interventions (strong recommendation, very low to moderate certainty), should form the foundation of care, with tailored therapy and support using shared decision-making based on the potential benefits, harms, certainty of evidence, and values and preferences of children and families. Pharmacologic and surgical interventions should be considered (conditional recommendation, low to moderate certainty) as therapeutic options based on availability, feasibility, and acceptability, and guided by shared decision-making between health care providers and families. This guideline will support children, families, and health care providers to have informed discussions about the balance of benefits and harms for available obesity management interventions to support value- and preference-sensitive decision-making.

暂无摘要（点击查看详情）

Concerns for anaphylaxis may hamper severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunization efforts. We convened a multidisciplinary group of international experts in anaphylaxis composed of allergy, infectious disease, emergency medicine, and front-line clinicians to systematically develop recommendations regarding SARS-CoV-2 vaccine immediate allergic reactions. Medline, EMBASE, Web of Science, the World Health Organizstion (WHO) global coronavirus database, and the gray literature (inception, March 19, 2021) were systematically searched. Paired reviewers independently selected studies addressing anaphylaxis after SARS-CoV-2 vaccination, polyethylene glycol (PEG) and polysorbate allergy, and accuracy of allergy testing for SARS-CoV-2 vaccine allergy. Random effects models synthesized the data to inform recommendations based on the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) approach, agreed upon using a modified Delphi panel. The incidence of SARS-CoV-2 vaccine anaphylaxis is 7.91 cases per million (n = 41,000,000 vaccinations; 95% confidence interval [95% CI] 4.02-15.59; 26 studies, moderate certainty), the incidence of 0.15 cases per million patient-years (95% CI 0.11-0.2), and the sensitivity for PEG skin testing is poor, although specificity is high (15 studies, very low certainty). We recommend vaccination over either no vaccination or performing SARS-CoV-2 vaccine/excipient screening allergy testing for individuals without history of a severe allergic reaction to the SARS-CoV-2 vaccine/excipient, and a shared decision-making paradigm in consultation with an allergy specialist for individuals with a history of a severe allergic reaction to the SARS-CoV-2 vaccine/excipient. We recommend further research to clarify SARS-CoV-2 vaccine/vaccine excipient testing utility in individuals potentially allergic to SARS-CoV2 vaccines or their excipients.

暂无摘要（点击查看详情）

To provide updated, evidence-based recommendations concerning the effects of dietary salt intake on the prevention and control of hypertension in adults (except pregnant women). The guidelines are intended for use in clinical practice and public education campaigns. Restriction of dietary salt intake may be an alternative to antihypertensive medications or may supplement such medications. Other options include other nonpharmacologic treatments for hypertension and no treatment. The health outcomes considered were changes in blood pressure and in morbidity and mortality rates. Because of insufficient evidence, no economic outcomes were considered. A MEDLINE search was conducted for the period 1966-1996 using the terms hypertension, blood pressure, vascular resistance, sodium chloride, sodium, diet, sodium or sodium chloride dietary, sodium restricted/reducing diet, clinical trials, controlled clinical trial, randomized controlled trial and random allocation. Both trials and review articles were obtained, and other relevant evidence was obtained from the reference lists of the articles identified, from the personal files of the authors and through contacts with experts. The articles were reviewed, classified according to study design and graded according to level of evidence. In addition, a systematic review of all published randomized controlled trials relating to dietary salt intake and hypertension was conducted. A high value was placed on the avoidance of cardiovascular morbidity and premature death caused by untreated hypertension. For normotensive people, a marked change in sodium intake is required to achieve a modest reduction in blood pressure (there is a decrease of 1 mm Hg in systolic blood pressure for every 100 mmol decrease in daily sodium intake). For hypertensive patients, the effects of dietary salt restriction are most pronounced if age is greater than 44 years. A decrease of 6.3 mm Hg in systolic blood pressure and 2.2 mm Hg in diastolic blood pressure per 100 mmol decrease in daily sodium intake was observed in people of this age group. For hypertensive patients 44 years of age and younger, the decreases were 2.4 mm Hg for systolic blood pressure and negligible for diastolic blood pressure. A diet in which salt is moderately restricted appears not to be associated with health risks. (1) Restriction of salt intake for the normotensive population is not recommended at present, because of insufficient evidence demonstrating that this would lead to a reduced incidence of hypertension. (2) To avoid excessive intake of salt, people should be counselled to choose foods low in salt (e.g., fresh fruits and vegetables), to avoid foods high in salt (e.g., pre-prepared foods), to refrain from adding salt at the table and minimize the amount of salt used in cooking, and to increase awareness of the salt content of food choices in restaurants. (3) For hypertensive patients, particularly those over the age of 44 years, it is recommended that the intake of dietary sodium be moderately restricted, to a target range of 90-130 mmol per day (which corresponds to 3-7 g of salt per day). (4) The salt consumption of hypertensive patients should be determined by interview. These recommendations were reviewed by all of the sponsoring organizations and by participants in a satellite symposium of the fourth International Conference on Preventive Cardiology. They have not been clinically tested. The Canadian Hypertension Society, the Canadian Coalition for High Blood Pressure Prevention and Control, the Laboratory Centre for Disease Control at Health Canada, and the Heart and Stroke Foundation of Canada.

Synthetic phenolic antioxidants have been added to foods for decades to retard the autooxidation of lipid that leads to rancidity. The major antioxidants, butylated hydroxytoluene (BHT) and butylated hydroxyanisole (BHA), are used in foods world wide. Recent studies suggest that BHA, and perhaps BHT, are carcinogenic to rodents. International efforts, including those at the HPB in Ottawa Canada, have helped place the results of the chronic rodent studies into perspective. It seems likely that the neoplastic effects observed at very high dietary levels of BHA and BHT occur only after effective biological defense mechanisms are overloaded. The renewed interest in the toxicity of phenols is beneficial to an understanding of the complex biological effects of naturally occurring phenolics, including reduction of the levels of reactive oxygen species that are associated with various disease states in an aging human population.

Over a 5-year interval, experiments were conducted to determine if Mycobacterium avium ssp. paratuberculosis (Map) is associated with in vivo and in vitro fertilized (IVF) embryos and whether it can be transmitted by embryo transfer. The present studies included: collection of embryos from five asymptomatic, naturally infected donors and transfer to uninfected recipients; collection of oocytes from two naturally infected donors with overt clinical signs; exposure of in vivo and IVF embryos to Map and transfer to uninfected recipients; and the inoculation (transfer) of "clean" IVF embryos to the uterine lumen of infected cows. The presence of Map was confirmed in the uterine horns of all asymptomatic, infected donors. None of the tested embryos, which were not used for embryo transfer, or unfertilized ova (two per batch), were positive for Map, as determined by culture (n = 19) or by PCR (n = 13). However, all in vivo fertilized embryos exposed to Map in vitro (and subsequently sequentially washed) tested positive for Map, by both culture (12 batches) and PCR (15 batches), whereas IVF embryos treated in the same manner tested positive on culture (51%, 18/35 batches) and by PCR (28%, 20/71 batches). Transferring both in vivo embryos and IVF embryos potentially contaminated with Map into 28 recipients resulted in 13 pregnancies and eight calves born without evidence of disease transmission to either the recipients or the offspring over the following 5-year period. In samples collected from one of the clinically infected animals, two of seven (28%) cumulus oocyte complexes (COC) and follicular fluid tested positive by PCR and 10/10 cumulus oocyte complexes on culture for Map. From the second clinically infected cow, three of five batches of IVF embryos (n = 20) were positive on PCR and two of four batches containing unfertilized oocytes and embryos were positive on culture. Only 10% of embryos reached the morula and blastocyst stage 10 days after fertilization. In conclusion, Map is unlikely to be transmitted by embryo transfer when the embryos have been washed as recommended by the International Embryo Transfer Society.

Food insecurity, defined as the lack of physical or economic access to safe, nutritious and sufficient food, remains one of the main challenges of the 2030 Agenda for Sustainable Development. Food insecurity is a complex phenomenon, resulting from the interplay of environmental, socio-demographic, and political events. Previous work has investigated the nexus between climate change, conflict, migration and food security at the household level, however these relations are still largely unexplored at national scales. In this context, during the Complexity72h workshop, held at the Universidad Carlos III de Madrid in June 2024, we explored the co-evolution of international migration flows and food insecurity at the national scale, accounting for remittances, as well as for changes in the economic, conflict, and climate situation. To this aim, we gathered data from several publicly available sources (Food and Agriculture Organization, World Bank, and UN Department of Economic and Social Affairs) and analyzed the association between food insecurity and migration, migration and remittances, and remittances and food insecurity. We then propose a framework linking together these association

Establishing a resilient food trade system is an international consensus on safeguarding food security amid growing disruptions. However, a unified resilience framework has yet to be established, leading to the proliferation of diverse measures. Here, we conceptualize resilience as a trade-off between efficiency and redundancy and employ an entropy-based approach to quantify the dynamic structural resilience of international trade networks for maize, rice, soybean, and wheat from 1986 to 2022. Using index decomposition analysis, we also investigate the relative contributions of internal components to resilience dynamics. Within this framework, despite heterogeneity across different food commodities, we find that current trade networks are relatively redundant, with improvements in efficiency being the dominant driver of changes in resilience. In addition, we reveal a historically pronounced impact of flow concentrations on resilience, while trade interactions have become increasingly important in recent years. Following the leave-one-out approach, we furthermore identify critical economies and trade relationships that disproportionately affect the overall resilience, some of which

The stability of the global food supply network is critical for ensuring food security. This study constructs an aggregated international food supply network based on the trade data of four staple crops and evaluates its structural robustness through network integrity under accumulating external shocks. Network integrity is typically quantified in network science by the relative size of the largest connected component, and we propose a new robustness metric that incorporates both the broadness p and severity q of external shocks. Our findings reveal that the robustness of the network has gradually increased over the past decades, punctuated by temporary declines that can be explained by major historical events. While the aggregated network remains robust under moderate disruptions, extreme shocks targeting key suppliers such as the United States and India can trigger systemic collapse. When the shock broadness p is less than about 0.3 and the shock severity q is close to 1, the structural robustness curves S(p,q) decrease linearly with respect to the shock broadness p, suggesting that the most critical economies have relatively even influence on network integrity. Comparing the rob

Food assistance referral requires conversational agents to translate underspecified, often noisy help-seeking dialogues into locally valid resource recommendations. We present Food4All, an agentic food-resource referral framework and benchmark grounded in 686 structured Indiana food resources. Food4All couples a food-specific search tool with 300 multi-turn evaluation tasks spanning single food needs, composite cases with access or document constraints, and five non-ideal user interaction traits: unreasonable demands, rambling responses, impatience, incomplete answers, and inconsistent information. We evaluate six Large Language Models (LLMs) on requirement grounding, resource retrieval, final referral correctness, and interaction efficiency. Although the strongest model achieves 96.33% referral accuracy, our diagnostics reveal persistent failures in grounding schedule, eligibility, intake, and document constraints, as well as failures to preserve valid retrieved resources in the final recommendation. Trait-level analysis further shows that different non-ideal behaviors stress different parts of the referral pipeline. Food4All provides a controlled testbed for studying tool-calling

This paper presents a scientometric analysis of research output from the University of Lagos, focusing on the two decades spanning 2004 to 2023. Using bibliometric data retrieved from the Web of Science, we examine trends in publication volume, collaboration patterns, citation impact, and the most prolific authors, departments, and research domains at the university. The study reveals a consistent increase in research productivity, with the highest publication output recorded in 2023. Health Sciences, Engineering, and Social Sciences are identified as dominant fields, reflecting the university's interdisciplinary research strengths. Collaborative efforts, both locally and internationally, show a positive correlation with higher citation impact, with the United States and the United Kingdom being the leading international collaborators. Notably, open-access publications account for a significant portion of the university's research output, enhancing visibility and citation rates. The findings offer valuable insights into the university's research performance over the past two decades, providing a foundation for strategic planning and policy formulation to foster research excellence

Research in the food domain is at times limited due to data sharing obstacles, such as data ownership, privacy requirements, and regulations. While important, these obstacles can restrict data-driven methods such as machine learning. Federated learning, the approach of training models on locally kept data and only sharing the learned parameters, is a potential technique to alleviate data sharing obstacles. This systematic review investigates the use of federated learning within the food domain, structures included papers in a federated learning framework, highlights knowledge gaps, and discusses potential applications. A total of 41 papers were included in the review. The current applications include solutions to water and milk quality assessment, cybersecurity of water processing, pesticide residue risk analysis, weed detection, and fraud detection, focusing on centralized horizontal federated learning. One of the gaps found was the lack of vertical or transfer federated learning and decentralized architectures.

The global food landscape is rife with scientific, cultural, and commercial claims about what foods are, what they do, what they should not do, or should not do. These range from rigorously studied health benefits (probiotics improve gut health) and misrepresentations (soaked almonds make one smarter) to vague promises (superfoods boost immunity) and culturally rooted beliefs (cold foods cause coughs). Despite their widespread influence, the infrastructure for tracing, verifying, and contextualizing these claims remains fragmented and underdeveloped. In this paper, we propose a Food Claim-Traceability Network (FCN) as an extension of FKG[.]in, a knowledge graph of Indian food that we have been incrementally building. We also present the ontology design and the semi-automated knowledge curation workflow that we used to develop a proof of concept of FKG[.]in-FCN using Reddit data and Large Language Models. FCN integrates curated data inputs, structured schemas, and provenance-aware pipelines for food-related claim extraction and validation. While directly linked to the Indian food knowledge graph as an application, our methodology remains application-agnostic and adaptable to other g

In this paper, we analyse the impact of international migration on the food consumption and dietary diversity of left-behind households. Using the Kerala migration survey 2011, we study whether households with emigrants (on account of international migration) have higher consumption expenditure and improved dietary diversity than their non-migrating counterparts. We use ordinary least square and instrumental variable approach to answer this question. The key findings are that: a) emigrant households have higher overall consumption expenditure as well as higher expenditure on food; b) we find that international migration leads to increase in the dietary diversity of left behind households. Further, we explore the effect on food sub-group expenditure for both rural and urban households. We find that emigrant households spend more on protein (milk, pulses and egg, fish and meat), at the same time there is higher spending on non-healthy food habits (processed and ready to eat food items) among them.

Price volatility in global food commodities is a critical signal indicating potential disruptions in the food market. Understanding forthcoming changes in these prices is essential for bolstering food security, particularly for nations at risk. The Food and Agriculture Organization of the United Nations (FAO) previously developed sophisticated statistical frameworks for the proactive prediction of food commodity prices, aiding in the creation of global early warning systems. These frameworks utilize food security indicators to produce accurate forecasts, thereby facilitating preparations against potential food shortages. Our research builds on these foundations by integrating robust price security indicators with cutting-edge deep learning (DL) methodologies to reveal complex interdependencies. DL techniques examine intricate dynamics among diverse factors affecting food prices. Through sophisticated time-series forecasting models coupled with a classification model, our approach enhances existing models to better support communities worldwide in advancing their food security initiatives.

In the European Union, official food safety monitoring data collected by member states are submitted to the European Food Safety Authority (EFSA) and published on Zenodo. This data includes 392 million analytical results derived from over 15.2 million samples covering more than 4,000 different types of food products, offering great opportunities for artificial intelligence to analyze trends, predict hazards, and support early warning systems. However, the current format with data distributed across approximately 1000 files totaling several hundred gigabytes hinders accessibility and analysis. To address this, we introduce the CompreHensive European Food Safety (CHEFS) database, which consolidates EFSA monitoring data on pesticide residues, veterinary medicinal product residues, and chemical contaminants into a unified and structured dataset. We describe the creation and structure of the CHEFS database and demonstrate its potential by analyzing trends in European food safety monitoring data from 2000 to 2024. Our analyses explore changes in monitoring activities, the most frequently tested products, which products were most often non-compliant and which contaminants were most often

We present Implicit-Scale 3D Reconstruction from Monocular Multi-Food Images, a benchmark dataset designed to advance geometry-based food portion estimation in realistic dining scenarios. Existing dietary assessment methods largely rely on single-image analysis or appearance-based inference, including recent vision-language models, which lack explicit geometric reasoning and are sensitive to scale ambiguity. This benchmark reframes food portion estimation as an implicit-scale 3D reconstruction problem under monocular observations. To reflect real-world conditions, explicit physical references and metric annotations are removed; instead, contextual objects such as plates and utensils are provided, requiring algorithms to infer scale from implicit cues and prior knowledge. The dataset emphasizes multi-food scenes with diverse object geometries, frequent occlusions, and complex spatial arrangements. The benchmark was adopted as a challenge at the MetaFood 2025 Workshop, where multiple teams proposed reconstruction-based solutions. Experimental results show that while strong vision--language baselines achieve competitive performance, geometry-based reconstruction methods provide both i

We present MM-Food-100K, a public 100,000-sample multimodal food intelligence dataset with verifiable provenance. It is a curated approximately 10% open subset of an original 1.2 million, quality-accepted corpus of food images annotated for a wide range of information (such as dish name, region of creation). The corpus was collected over six weeks from over 87,000 contributors using the Codatta contribution model, which combines community sourcing with configurable AI-assisted quality checks; each submission is linked to a wallet address in a secure off-chain ledger for traceability, with a full on-chain protocol on the roadmap. We describe the schema, pipeline, and QA, and validate utility by fine-tuning large vision-language models (ChatGPT 5, ChatGPT OSS, Qwen-Max) on image-based nutrition prediction. Fine-tuning yields consistent gains over out-of-box baselines across standard metrics; we report results primarily on the MM-Food-100K subset. We release MM-Food-100K for publicly free access and retain approximately 90% for potential commercial access with revenue sharing to contributors.