Magnesium plays an important role in many physiological functions. Habitually low intakes of magnesium and in general the deficiency of this micronutrient induce changes in biochemical pathways that can increase the risk of illness and, in particular, chronic degenerative diseases. The assessment of magnesium status is consequently of great importance, however, its evaluation is difficult. The measurement of serum magnesium concentration is the most commonly used and readily available method for assessing magnesium status, even if serum levels have no reliable correlation with total body magnesium levels or concentrations in specific tissues. Therefore, this review offers an overview of recent insights into magnesium from multiple perspectives. Starting from a biochemical point of view, it aims at highlighting the risk due to insufficient uptake (frequently due to the low content of magnesium in the modern western diet), at suggesting strategies to reach the recommended dietary reference values, and at focusing on the importance of detecting physiological or pathological levels of magnesium in various body districts, in order to counteract the social impact of diseases linked to magnesium deficiency.
Jana G. Hashash, Jaclyn R Elkins, James D. Lewis
et al.
DESCRIPTION Diet plays a critical role in human health, but especially for patients with inflammatory bowel disease (IBD). Guidance about diet for patients with IBD are often controversial and a source of uncertainty for many physicians and patients. The role of diet has been investigated as a risk factor for IBD etiopathogenesis and as a therapy for active disease. Dietary restrictions, along with the clinical complications of IBD, can result in malnutrition, an underrecognized condition among this patient population. The aim of this American Gastroenterological Association (AGA) Clinical Practice Update (CPU) is to provide best practice advice statements, primarily to clinical gastroenterologists, covering the topics of diet and nutritional therapies in the management of IBD, while emphasizing identification and treatment of malnutrition in these patients. We provide guidance for tailored dietary approaches during IBD remission, active disease, and intestinal failure. A healthy Mediterranean diet will benefit patients with IBD, but may require accommodations for food texture in the setting of intestinal strictures or obstructions. New data in Crohn's disease supports the use of enteral liquid nutrition to help induce remission and correct malnutrition in patients heading for surgery. Parenteral nutrition plays a critical role in patients with IBD facing acute and/or chronic intestinal failure. Registered dietitians are an essential part of the interdisciplinary team approach for optimal nutrition assessment and management in the patient population with IBD. METHODS This expert review was commissioned and approved by the AGA Clinical Practice Updates Committee and the AGA Governing Board to provide timely guidance on a topic of high clinical importance to the AGA membership and underwent internal peer review by the CPU Committee and external peer review through standard procedures of Gastroenterology. The best practice advice statements were drawn from reviewing existing literature combined with expert opinion to provide practical advice on the role of diet and nutritional therapies in patients with IBD. Because this was not a systematic review, formal rating of the quality of evidence or strength of the presented considerations was not performed. Best Practice Advice Statements BEST PRACTICE ADVICE 1: Unless there is a contraindication, all patients with IBD should be advised to follow a Mediterranean diet rich in a variety of fresh fruits and vegetables, monounsaturated fats, complex carbohydrates, and lean proteins and low in ultraprocessed foods, added sugar, and salt for their overall health and general well-being. No diet has consistently been found to decrease the rate of flares in adults with IBD. A diet low in red and processed meat may reduce ulcerative colitis flares, but has not been found to reduce relapse in Crohn's disease. BEST PRACTICE ADVICE 2: Patients with IBD who have symptomatic intestinal strictures may not tolerate fibrous, plant-based foods (ie, raw fruits and vegetables) due to their texture. An emphasis on careful chewing and cooking and processing of fruits and vegetables to a soft, less fibrinous consistency may help patients with IBD who have concomitant intestinal strictures incorporate a wider variety of plant-based foods and fiber in their diets. BEST PRACTICE ADVICE 3: Exclusive enteral nutrition using liquid nutrition formulations is an effective therapy for induction of clinical remission and endoscopic response in Crohn's disease, with stronger evidence in children than adults. Exclusive enteral nutrition may be considered as a steroid-sparing bridge therapy for patients with Crohn's disease. BEST PRACTICE ADVICE 4: Crohn's disease exclusion diet, a type of partial enteral nutrition therapy, may be an effective therapy for induction of clinical remission and endoscopic response in mild to moderate Crohn's disease of relatively short duration. BEST PRACTICE ADVICE 5: Exclusive enteral nutrition may be an effective therapy in malnourished patients before undergoing elective surgery for Crohn's disease to optimize nutritional status and reduce postoperative complications. BEST PRACTICE ADVICE 6: In patients with IBD who have an intra-abdominal abscess and/or phlegmonous inflammation that limits ability to achieve optimal nutrition via the digestive tract, short-term parenteral nutrition may be used to provide bowel rest in the preoperative phase to decrease infection and inflammation as a bridge to definitive surgical management and to optimize surgical outcomes. BEST PRACTICE ADVICE 7: We suggest the use of parenteral nutrition for high-output gastrointestinal fistula, prolonged ileus, short bowel syndrome, and for patients with IBD with severe malnutrition when oral and enteral nutrition has been trialed and failed or when enteral access is not feasible or contraindicated. BEST PRACTICE ADVICE 8: In patients with IBD and short bowel syndrome, long-term parenteral nutrition should be transitioned to customized hydration management (ie, intravenous electrolyte support and/or oral rehydration solutions) and oral intake whenever possible to decrease the risk of developing long-term complications. Treatment with glucagon-like peptide-2 agonists can facilitate this transition. BEST PRACTICE ADVICE 9: All patients with IBD warrant regular screening for malnutrition by their provider by means of assessing signs and symptoms, including unintended weight loss, edema and fluid retention, and fat and muscle mass loss. When observed, more complete evaluation for malnutrition by a registered dietitian is indicated. Serum proteins are no longer recommended for the identification and diagnosis of malnutrition due to their lack of specificity for nutritional status and high sensitivity to inflammation. BEST PRACTICE ADVICE 10: All patients with IBD should be monitored for vitamin D and iron deficiency. Patients with extensive ileal disease or prior ileal surgery (resection or ileal pouch) should be monitored for vitamin B12 deficiency. BEST PRACTICE ADVICE 11: All outpatients and inpatients with complicated IBD warrant co-management with a registered dietitian, especially those who have malnutrition, short bowel syndrome, enterocutaneous fistula, and/or are requiring more complex nutrition therapies (eg, parenteral nutrition, enteral nutrition, or exclusive enteral nutrition), or those on a Crohn's disease exclusion diet. We suggest that all newly diagnosed patients with IBD have access to a registered dietitian. BEST PRACTICE ADVICE 12: Breastfeeding is associated with a lower risk for diagnosis of IBD during childhood. A healthy, balanced, Mediterranean diet rich in a variety of fruits and vegetables and decreased intake of ultraprocessed foods have been associated with a lower risk of developing IBD.
The WHO has recognised iron deficiency anaemia (IDA) as the most common nutritional deficiency in the world, with 30% of the population being affected with this condition. Although the most common causes of IDA are gastrointestinal bleeding and menstruation in women, decreased dietary iron and decreased iron absorption are also culpable causes. Patients with IDA should be treated with the aim of replenishing iron stores and returning the haemoglobin to a normal level. This has shown to improve quality of life, morbidity, prognosis in chronic disease and outcomes in pregnancy. Iron deficiency occurs in many chronic inflammatory conditions, including congestive cardiac failure, chronic kidney disease and inflammatory bowel disease. This article will provide an updated overview on diagnosis and management of IDA in patients with chronic conditions, preoperative and in pregnancy. We will discuss the benefits and limitations of oral versus intravenous iron replacement in each cohort, with an overview on cost analysis between the different iron formulations currently on the market.
Awuchi Godswill Godswill, Igwe Victory Somtochukwu, Amagwula O Ikechukwu
et al.
The research focused on the benefits of micronutrients (vitamins and minerals) and their associated deficiency diseases and health complications. Micronutrients are essential elements required by human and other organisms in varying quantities throughout life to coordinate a range of physiological functions for health maintenance. For human nutrition, micronutrients are required in amounts generally below 100 milligrams per day, while macronutrients are required in gram amounts daily. Vitamins and minerals are essential micronutrients. Essential nutrients cannot be synthesized in humans, either at all or may be in insufficient amounts, and therefore must be obtained by the diet. Vitamin C can be synthesized by some organisms but not by others; it is not a vitamin in the first instance but is in the second. In humans there are 13 vitamins: 9 water-soluble (8 B vitamins and vitamin C) and 4 fat-soluble (A, D, E, and K). Vitamins A and D can amass in the body, which may result in dangerous hypervitaminosis. Anti-vitamins inhibit the actions or absorption of vitamins; avidin inhibits biotin absorption, although it is deactivated by cooking; Pyrithiamine inhibits enzymes that use vitamin B1. The four key structural elements in human body (oxygen, hydrogen, carbon, and nitrogen) by weight, are often not included in the lists of major nutrient minerals (nitrogen is a "mineral" for plants, as it is often included in fertilizers). These four key elements compose around 96% of the weight of human body, and the major minerals (macrominerals) and minor minerals (trace elements) compose the remaining percent. The five major minerals in the the human body are calcium, phosphorus, potassium, sodium, and magnesium (macrominerals or macroelements). The trace elements with specific biochemical function in human body are iodine, sulfur, zinc, iron, chlorine, cobalt, copper, manganese, molybdenum, and selenium. Calcium makes up 920 to 1200 g of body weight (about 1.5% of body weight) of an adult, with 99% of it contained in the bones and teeth. Phosphorus occurs in amounts of around 2/3 of calcium, and makes up approximately 1% of an individual's body weight. The other macroelements (potassium, sodium, magnesium, chlorine, and sulfur) make up only around 0.85% of the body weight
Md Hasan Hafizur Rahman, Ishita Mostafa, Jafrin Ferdous
et al.
Abstract
Objective:
This study used the trials of improved practices (TIPs) approach to explore complementary feeding practices among caregivers of children under two and assess the acceptance of new nutritional supplements by providing microbiota-directed supplementary food (MDSF), ready-to-use supplementary food (RUSF) and locally available food (LAF) among moderately malnourished children.
Design:
The study was conducted between May and October 2022 in preparation for a larger trial. The first phase focused on complementary feeding, hygiene, breast-feeding and responsive feeding practices using in-depth interviews and observations. The second phase involved counselling sessions and providing food supplements for forty-five participants. Follow-up visits evaluated acceptability and challenges faced during this period.
Setting:
Bauniabadh slum, Mirpur, Dhaka.
Participants:
Sixty-five children aged 6–24 months with moderate wasting and their caregivers.
Results:
Findings from IDI and observations revealed poor handwashing practices, with most caregivers washing only with water, and inconsistent use of soap. Only a minority boiled drinking water or cleaned utensils with soap. Responsive feeding practices were also limited, with frequent mobile phone use during feeding and lack of attention to the child. Among the three food interventions, LAF received the highest hedonic ratings across all sensory attributes, with a mean taste score of 5·7±1·4, compared with MDSF (4·8±1·9) and RUSF (4·7±1·6), although median consumption was similar across all supplements (75%).
Conclusion:
The TIPs approach identified context-specific caregiver behaviours and feeding preferences. These findings will guide the upcoming trial and assist policymakers and program planners in developing culturally tailored interventions to address childhood malnutrition in urban slums.
Public aspects of medicine, Nutritional diseases. Deficiency diseases
Crop yield production could be enhanced for agricultural growth if various plant nutrition deficiencies, and diseases are identified and detected at early stages. Hence, continuous health monitoring of plant is very crucial for handling plant stress. The deep learning methods have proven its superior performances in the automated detection of plant diseases and nutrition deficiencies from visual symptoms in leaves. This article proposes a new deep learning method for plant nutrition deficiencies and disease classification using a graph convolutional network (GNN), added upon a base convolutional neural network (CNN). Sometimes, a global feature descriptor might fail to capture the vital region of a diseased leaf, which causes inaccurate classification of disease. To address this issue, regional feature learning is crucial for a holistic feature aggregation. In this work, region-based feature summarization at multi-scales is explored using spatial pyramidal pooling for discriminative feature representation. Furthermore, a GCN is developed to capacitate learning of finer details for classifying plant diseases and insufficiency of nutrients. The proposed method, called Plant Nutrition Deficiency and Disease Network (PND-Net), has been evaluated on two public datasets for nutrition deficiency, and two for disease classification using four backbone CNNs. The best classification performances of the proposed PND-Net are as follows: (a) 90.00% Banana and 90.54% Coffee nutrition deficiency; and (b) 96.18% Potato diseases and 84.30% on PlantDoc datasets using Xception backbone. Furthermore, additional experiments have been carried out for generalization, and the proposed method has achieved state-of-the-art performances on two public datasets, namely the Breast Cancer Histopathology Image Classification (BreakHis 40×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times $$\end{document}: 95.50%, and BreakHis 100×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times $$\end{document}: 96.79% accuracy) and Single cells in Pap smear images for cervical cancer classification (SIPaKMeD: 99.18% accuracy). Also, the proposed method has been evaluated using five-fold cross validation and achieved improved performances on these datasets. Clearly, the proposed PND-Net effectively boosts the performances of automated health analysis of various plants in real and intricate field environments, implying PND-Net’s aptness for agricultural growth as well as human cancer classification.
Malnutrition is an important issue in patients with inflammatory bowel diseases (IBDs) including Crohn’s disease (CD) and ulcerative colitis (UC). It is caused by altered digestion and absorption within the small bowel, inadequate food intake, and drug–nutrient interactions in patients. Malnutrition is an essential problem because it is related to an increased risk of infections and poor prognosis in patients. It is known that malnutrition is also related to an increased risk of postsurgery complications in IBD patients. Basic nutritional screening involves anthropometric parameters with body mass index (BMI) and others (fat mass, waist-to-hip ratio, muscle strength), medical history concerning weight loss, and biochemical parameters (including the Prognostic Nutritional Index). Besides standard nutritional screening tools, including the Subjective Global Assessment (SGA), Nutritional Risk Score 2002 (NRS 2002), and Malnutrition Universal Screening Tool (MUST), specific nutritional screening tools are used in IBD patients, such as the Saskatchewan Inflammatory Bowel Disease–Nutrition Risk Tool (SaskIBD-NR Tool and IBD-specific Nutritional Screening Tool). There is a higher risk of nutrient deficiencies (including iron, zinc, magnesium) and vitamin deficiencies (including folic acid, vitamin B12 and D) in IBD patients. Therefore, regular evaluation of nutritional status is important in IBD patients because many of them are undernourished. An association between plasma ghrelin and leptin and nutritional status in IBD patients has been observed. According to some authors, anti-tumor necrosis factor (anti-TNFα) therapy (infliximab) can improve nutritional status in IBD patients. On the other hand, improvement in nutritional status may increase the response rate to infliximab therapy in CD patients. Optimization of nutritional parameters is necessary to improve results of conservative and surgical treatment and to prevent postoperative complications in patients with IBDs. This review presents basic nutritional screening tools, anthropometric and laboratory parameters, dietary risk factors for IBDs, common nutrient deficiencies, associations between anti-TNFα therapy and nutritional status, selected features regarding the influence of nutritional status, and surgical outcome in IBD patients.
Bosubabu Sambana, Hillary Sunday Nnadi, Mohd Anas Wajid
et al.
Plant diseases pose significant challenges to farmers and the agricultural sector at large. However, early detection of plant diseases is crucial to mitigating their effects and preventing widespread damage, as outbreaks can severely impact the productivity and quality of crops. With advancements in technology, there are increasing opportunities for automating the monitoring and detection of disease outbreaks in plants. This study proposed a system designed to identify and monitor plant diseases using a transfer learning approach. Specifically, the study utilizes YOLOv7 and YOLOv8, two state-ofthe-art models in the field of object detection. By fine-tuning these models on a dataset of plant leaf images, the system is able to accurately detect the presence of Bacteria, Fungi and Viral diseases such as Powdery Mildew, Angular Leaf Spot, Early blight and Tomato mosaic virus. The model's performance was evaluated using several metrics, including mean Average Precision (mAP), F1-score, Precision, and Recall, yielding values of 91.05, 89.40, 91.22, and 87.66, respectively. The result demonstrates the superior effectiveness and efficiency of YOLOv8 compared to other object detection methods, highlighting its potential for use in modern agricultural practices. The approach provides a scalable, automated solution for early any plant disease detection, contributing to enhanced crop yield, reduced reliance on manual monitoring, and supporting sustainable agricultural practices.
Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing dermatology. Generative AI and machine learning approaches offer opportunities to enhance the diagnosis and treatment of inflammatory skin diseases, including atopic dermatitis, psoriasis, hidradenitis suppurativa, and autoimmune connective tissue disease. This review examines the current landscape of AI applications for inflammatory skin diseases and explores how generative AI and machine learning methods can advance the field through deep phenotyping, disease heterogeneity characterization, drug development, personalized medicine, and clinical care. We discuss the promises and challenges of these technologies and present a vision for their integration into clinical practice.
Magnesium (Mg2+) has many physiological functions within the body. These include important roles in maintaining cardiovascular functioning, where it contributes to the regulation of cardiac excitation–contraction coupling, endothelial functioning and haemostasis. The haemostatic roles of Mg2+ impact upon both the protein and cellular arms of coagulation. In this review, we examine how Mg2+ homeostasis is maintained within the body and highlight the various molecular roles attributed to Mg2+ in the cardiovascular system. In addition, we describe how nutritional and/or disease-associated magnesium deficiency, seen in some metabolic conditions, has the potential to influence cardiac and vascular outcomes. Finally, we also examine the potential for magnesium supplements to be employed in the prevention and treatment of cardiovascular disorders and in the management of cardiometabolic health.
Md Aziz Hosen Foysal, Foyez Ahmed, Md Zahurul Haque
Plant diseases significantly impact agricultural productivity, resulting in economic losses and food insecurity. Prompt and accurate detection is crucial for the efficient management and mitigation of plant diseases. This study investigates advanced techniques in plant disease detection, emphasizing the integration of image processing, machine learning, deep learning methods, and mobile technologies. High-resolution images of plant leaves were captured and analyzed using convolutional neural networks (CNNs) to detect symptoms of various diseases, such as blight, mildew, and rust. This study explores 14 classes of plants and diagnoses 26 unique plant diseases. We focus on common diseases affecting various crops. The model was trained on a diverse dataset encompassing multiple crops and disease types, achieving 98.14% accuracy in disease diagnosis. Finally integrated this model into mobile apps for real-time disease diagnosis.
Pumpkin is a vital crop cultivated globally, and its productivity is crucial for food security, especially in developing regions. Accurate and timely detection of pumpkin leaf diseases is essential to mitigate significant losses in yield and quality. Traditional methods of disease identification rely heavily on subjective judgment by farmers or experts, which can lead to inefficiencies and missed opportunities for intervention. Recent advancements in machine learning and deep learning offer promising solutions for automating and improving the accuracy of plant disease detection. This paper presents a comprehensive analysis of state-of-the-art Convolutional Neural Network (CNN) models for classifying diseases in pumpkin plant leaves. Using a publicly available dataset of 2000 highresolution images, we evaluate the performance of several CNN architectures, including ResNet, DenseNet, and EfficientNet, in recognizing five classes: healthy leaves and four common diseases downy mildew, powdery mildew, mosaic disease, and bacterial leaf spot. We fine-tuned these pretrained models and conducted hyperparameter optimization experiments. ResNet-34, DenseNet-121, and EfficientNet-B7 were identified as top-performing models, each excelling in different classes of leaf diseases. Our analysis revealed DenseNet-121 as the optimal model when considering both accuracy and computational complexity achieving an overall accuracy of 86%. This study underscores the potential of CNNs in automating disease diagnosis for pumpkin plants, offering valuable insights that can contribute to enhancing agricultural productivity and minimizing economic losses.
Plant diseases pose significant threats to agriculture. It necessitates proper diagnosis and effective treatment to safeguard crop yields. To automate the diagnosis process, image segmentation is usually adopted for precisely identifying diseased regions, thereby advancing precision agriculture. Developing robust image segmentation models for plant diseases demands high-quality annotations across numerous images. However, existing plant disease datasets typically lack segmentation labels and are often confined to controlled laboratory settings, which do not adequately reflect the complexity of natural environments. Motivated by this fact, we established PlantSeg, a large-scale segmentation dataset for plant diseases. PlantSeg distinguishes itself from existing datasets in three key aspects. (1) Annotation type: Unlike the majority of existing datasets that only contain class labels or bounding boxes, each image in PlantSeg includes detailed and high-quality segmentation masks, associated with plant types and disease names. (2) Image source: Unlike typical datasets that contain images from laboratory settings, PlantSeg primarily comprises in-the-wild plant disease images. This choice enhances the practical applicability, as the trained models can be applied for integrated disease management. (3) Scale: PlantSeg is extensive, featuring 11,400 images with disease segmentation masks and an additional 8,000 healthy plant images categorized by plant type. Extensive technical experiments validate the high quality of PlantSeg's annotations. This dataset not only allows researchers to evaluate their image classification methods but also provides a critical foundation for developing and benchmarking advanced plant disease segmentation algorithms.
The emerging research shows that lncRNAs are associated with a series of complex human diseases. However, most of the existing methods have limitations in identifying nonlinear lncRNA-disease associations (LDAs), and it remains a huge challenge to predict new LDAs. Therefore, the accurate identification of LDAs is very important for the warning and treatment of diseases. In this work, multiple sources of biomedical data are fully utilized to construct characteristics of lncRNAs and diseases, and linear and nonlinear characteristics are effectively integrated. Furthermore, a novel deep learning model based on graph attention automatic encoder is proposed, called HGATELDA. To begin with, the linear characteristics of lncRNAs and diseases are created by the miRNA-lncRNA interaction matrix and miRNA-disease interaction matrix. Following this, the nonlinear features of diseases and lncRNAs are extracted using a graph attention auto-encoder, which largely retains the critical information and effectively aggregates the neighborhood information of nodes. In the end, LDAs can be predicted by fusing the linear and nonlinear characteristics of diseases and lncRNA. The HGATELDA model achieves an impressive AUC value of 0.9692 when evaluated using a 5-fold cross-validation indicating its superior performance in comparison to several recent prediction models. Meanwhile, the effectiveness of HGATELDA in identifying novel LDAs is further demonstrated by case studies. the HGATELDA model appears to be a viable computational model for predicting LDAs.
Kimia Haji Ali Pashaei, Zahra Namkhah, Seyyed Reza Sobhani
Abstract Background The metabolic syndrome (MetS) comprises metabolic irregularities, including hypertension and central obesity, which are influenced by genetic, metabolic, environmental, and dietary factors. As diet and lifestyle are risk factors for MetS, it is important to know which diet quality index better predicts MetS. The aim of this study is to compare the ability of different diet quality indices in predicting MetS and to identify the most effective one. Methods This cross-sectional study involved 5,206 participants aged 35 to 70 engaged in the Prospective Epidemiological Research Study in Iran (PERSIAN) cohort. Assessment of one year’s food intake via a validated 134-item semi-quantitative food frequency questionnaire (FFQ) facilitated the calculation of adherence to five diet quality indices: Dietary Approaches to Stop Hypertension (DASH), Mediterranean, Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND), Dietary Inflammatory Index (DII), and Diet Quality Indices (DQI). While bivariate Pearson correlation and binary logistic regression aided in identifying the strongest correlation and predictor for MetS among the indices. Results This study showed a significant association between adhering to the DASH diet score, Mediterranean diet score, MIND diet score, DII score, and DQI score, and the odds of developing MetS (OR: 0.94, (95% CI: 0.93–0.95), OR: 0.85, (95% CI: 0.81–0.89), OR: 0.84, (95% CI: 0.80–0.89), OR: 1.22, (95%CI: 1.11–1.34), OR: 0.95, (95%CI 0.94–0.96) respectively). Therefore, with each unit increase in DASH diet score, Mediterranean diet score, MIND diet score, DII score, and DQI score, the odds of MetS was reduced by 5.4%, 14.5%, 15.6%, 22%, 5%, respectively. All the indices were correlated with the intake of most of the micronutrients, with the strongest correlations being observed in the DII. DASH diet score aligned with the most favourable MetS biomarker risk, while DII score primarily associated with MetS and could be considered as a predictor for MetS. Conclusion The present study’s findings reveal that between all these five diet quality indices, the DASH diet score correlates strongly with a favourable biomarker risk profile, while the DII score is predominantly linked to MetS.
Heitor Bernardes Pereira Delfino, Marcela Augusta de Souza Pinhel, Flávia Campos Ferreira
et al.
Obesity is a complex disease with a multifactorial etiology and could be associated with psychiatric disorders, such as Binge Eating Disorder (BED), characterized by recurrent episodes of binge eating in the absence of compensatory behaviors. The present study aimed to analyze anthropometric and body composition changes over five years after bariatric surgery in patients diagnosed or not diagnosed with BED, depression, and anxiety in the preoperative period. One hundred and eighteen patients undergoing bariatric surgery were evaluated and divided into two groups according to the presence or absence of BED. The patients were submitted to anthropometric and body composition evaluation. We also analyzed BED diagnosis, depression, and anxiety according to the DSM-5 and validated questionnaires. The Kolmogorov–Smirnov, <i>t</i>-test, Fisher’s, and chi-square tests were used for statistical analysis. Over five years after bariatric surgery, only the BED group exhibited an increased weight and BMI (<i>p</i> < 0.05). In the preoperative period, patients with BED had severe depression (13,11%, <i>p</i> = 0.0079) and a higher frequency of moderate (22.95%, <i>p</i> < 0.01) or severe (14.75%, <i>p</i> < 0.01) anxiety. In conclusion, patients with BED had more intense symptoms of depression and anxiety in the preoperative period, and this disorder may persist in the postoperative period of bariatric surgery, contributing to weight gain and increased BMI.
Food processing and manufacture, Nutritional diseases. Deficiency diseases