Calorie Count Research Articles

Abstract TP149: Development and Implementation of an Algorithm for Early Percutaneous Endoscopic Gastrostomy (PEG) Tube Placement in Acute Stroke Patients

Background: Dysphagia is a common complication of stroke and often leads to the need for modified diets and alternate feeding routes. Length of stay (LOS) for stroke patients requiring percutaneous endoscopic gastrostomy (PEG) tubes is often longer than those who can eat by mouth. The decision to place a PEG is multifactorial and multidisciplinary, involving speech-language pathologist (SLP), dietary, and neurology input, as well as goals of care. Despite this complex decision-making process, there are few existing algorithms to guide the need and timing for PEG placement. Hypothesis: Use of a PEG algorithm will result in timelier PEG placement and shorter LOS for acute stroke patients requiring artificial nutrition. Methods: A multidisciplinary team, including physicians, nurses, registered dieticians, and SLPs designed an evidenced based algorithm to guide PEG placement. Based on assessment and individual patient factors, possible algorithm pathways included dysphagia treatment and/or calorie count by nursing and dieticians to guide decision-making for PEG placement. A retrospective study was conducted in the inpatient setting of a comprehensive stroke center. Data included 68 acute ischemic and hemorrhagic stroke patients admitted to the Neurology and Neurosurgery services from 1/1/2023-2/29/24. Only those patients who were identified as being at risk for significant oropharyngeal dysphagia, aspiration pneumonia, and/or malnutrition were included in the study. Data collected included age, diet recommendation, and initial National Institutes of Health Stroke Scale Score with a focus on length of time from PEG recommendation to PEG placement and LOS. Statistical analysis was completed via t-test. Results: Comparing algorithm (n=30) and non-algorithm (n=38) groups, there was an average decrease of 3.86 days from PEG recommendation to placement in the algorithm group. Although this was not statistically significant (p=0.211), this resulted in decreased LOS from 24.2 to 20.0 days and hospital savings of ~ $7,720 per patient. Conclusions: Implementation of a multidisciplinary PEG algorithm resulted in reduced time from PEG recommendation to placement and shorter LOS. This novel process helped to guide decision-making for timelier PEG placement. Ongoing studies will be powered to assess overall impact on LOS, costs, outcomes, and complications.

Protocol of an Efficacy Study on Nursing Consultation in Weight Management and Metabolic Syndrome Based on the Carbohydrate-Insulin Theory in Individuals with First-Episode Psychosis.

Background: Individuals with severe mental illness live, on average, up to 30 years less than the general population, with cardiovascular disease being the leading cause of death. Metabolic syndrome (MetS) plays a significant role in this, making it crucial to manage this issue in individuals with psychosis at the onset of the illness. The approach to managing this issue has evolved from a focus on calorie counting to a deeper understanding of hormone function, particularly the role of insulin resistance in MetS. Therefore, incorporating this perspective into mental health nursing consultations with individuals experiencing psychosis is of great interest. Methods: In accordance with the SPIRIT guidelines, an open randomized clinical trial is proposed, involving patients from a first-episode psychosis program. Results: The primary outcome will be significant weight loss (≥5%). Secondary outcomes will include changes in metabolic parameters, psychopathological status, quality of life, and physical activity. Participants will be assigned to two groups: one group will attend a series of six previously manualized nursing consultations, while the other will continue with their usual treatment. Results will be evaluated at six months and one year. Conclusions: This study will determine whether a mental health nursing consultation based on the carbohydrate-insulin model of obesity is effective in reducing weight and the risk of MetS in individuals with early-onset psychosis. This study was retrospectively registered on Clinical Trials-NCT06650943.

An Image-Recognition Dietary Assessment App for Adolescents With Obesity: Pilot Randomized Controlled Trial.

Adolescence is a period of increased susceptibility to developing obesity-related health issues due to poor eating patterns and increased sedentary behaviors. Recommendations for pediatric obesity management include dietary assessments. However, adolescents often avoid food logging through traditional methods. The use of image-recognition dietary assessment apps in adolescents with obesity is not well studied. Eating for Wellness (E4W) is a mobile app that determines the nutritional content of meals from photos and incorporates nutritional goal setting. Nutritional data can be displayed for health care providers (HCPs) via the Clinician Portal, while the data are presented to the user in a manner that minimizes the focus on calorie counting. This study aims to evaluate the usability and feasibility of E4W, a mobile health app designed to improve dietary intake in adolescents with obesity attending an obesity clinic, using a phased approach. The overall study was conducted in 2 phases to refine and evaluate E4W. In Phase 1, usability was tested through 3 iterative cycles of patient interviews. A total of 14 patient participants, aged 12-18 years with a BMI≥97th percentile, were included. Participants performed standardized scenario-based tasks in E4W and provided feedback on the app. Two iterative cycles were conducted for HCPs (n=4). Refinements were made during each cycle based on issues encountered and feedback provided. In Phase 2, a pilot randomized controlled trial of 32 adolescents (16 adolescents enrolled in the experimental group for 1 month, and 16 controls enrolled for 1 month) was completed. Both groups met with their dietitian at baseline, midstudy, and 1 month following their baseline visit to discuss goals and eating patterns. The control group was instructed to take photos of all intake using their default phone camera, without access to E4W, while those in the experimental group received full access to E4W. The primary outcome was the feasibility of implementation. Secondary outcomes examined overall change in dietary intake and achievement of nutritional goals. Usability testing demonstrated that E4W and the Clinician Portal were easy to use, efficient, and well-liked by patients and HCPs. Feasibility testing revealed high patient acceptability scores. However, significant technical challenges were encountered. Although the use of E4W did not significantly impact patient engagement (control: mean 0.9, SD 0.7; experimental: mean 1.7, SD 1.9; P=.14), there were outliers in the experimental group with very high engagement and improved self-reported efficacy. Overall, there was no improvement in dietary intake, although assessment was hindered by poor adherence to traditional methods of food logging. E4W and the Clinician Portal were well-received by patients and HCPs. Further research is warranted and planned to determine if E4W can improve dietary intake and achievement of nutritional goals in adolescents with obesity. ClinicalTrials.gov NCT05548868; https://clinicaltrials.gov/study/NCT05548868.

Enhancing Broccoli growth by bacillus rhizosphere bacteria

This study examines the enhancement of broccoli growth by Bacillus Rhizosphere. Bacteria Broccoli is a nutrient-rich vegetable known for its high content of polyphenols, flavonoids, vitamins, minerals, fiber, and low calorie count, making it a recommended daily food. Tropical regions grow broccoli in mountainous areas. Sustainable agriculture emphasizes minimizing chemical fertilizers, and biofertilizers like Plant Growth Promoting Rhizobacteria (PGPR), such as Bacillus, can reduce their use. Bacillus improves plant growth by fixing nitrogen, solubilizing phosphate and potassium, and producing phytohormones. Understanding Bacillus growth dynamics is vital for optimizing its agricultural application. This study aimed to analyze growth curves of different Bacillus species and investigate their potential role in promoting broccoli growth. This study was carried out in January–April 2024 at the Soil Biology Laboratory, Faculty of Agriculture, Universitas Padjadjaran, and Bumi Agro Technology Company, Lembang. The research was divided into 3 stages: growth curve determination, Bacillus liquid inoculant preparation, and application of treatment to plants. The findings showed that isolates of B. safensis strain MDL5, B. altitudinis strain RPW2, B. subtilis strain YPS4, and Bacillus sp. strain SZ057 reached the highest point in their growth curves after 4 and 5 days of incubation. After that, the curves slowly went down. Inoculating Bacillus into broccoli plants resulted in an increase in plant height by 43.28–58.75% compared to the control.

Comprehensive Review on BMI, TDEE, BMR, and Calories for Weight Management: Insights into Energy Expenditure and Nutrient Balance for Long-Term Well-Being

Body Mass Index (BMI) is a basic tool for assessing body mass based on height and weight, classifying individuals in BMI categories as underweight, normal, overweight, or obese. However, it has limitations as it overlooks muscle mass and fat distribution. Total Daily Energy Expenditure (TDEE) plays a crucial role in measuring the current maintenance calories, surplus calories for weight gain, and deficit calories for weight loss associated with Bansal Metabolic Rate (BMR) and Physical Activity Level (PAL). TDEE is related to 3 phases incline, stable, and decline according to age groups. Keeping these parameters, the current review focused on BMI, TDEE, BMR and calories. Calories are essential for understanding the energy the body stores and uses, making them a key factor for weight management. Macronutrients such as carbohydrates, proteins, and fats provide different amounts of energy, which can impact insulin levels and trigger cravings. Tools like BMI and BMR are useful, but focusing solely on counting calories is not enough for effective weight management. A sustainable approach includes understanding how the body processes different foods, choosing nutrient-rich options, regulating blood sugar, and staying physically active are discussed. This work reveals the long-term well-being for weight management via focused on BMI, TDEE, BMR and calories.

The Role of Calorie Counts in the Acute Care Setting

The Role of Calorie Counts in the Acute Care Setting

Food Calories Generator through Deep Learning

Identifying food and calculating calories are key components of encouraging good eating habits and controlling dietary intake. These days, it's easier to create smart systems that can recognize food items from images or videos and calculate their calorie content using artificial intelligence, computer vision, and machine learning. This study gives an overview of the latest methods and tools for calorie counting and food identification. It looks at the challenges of accurately identifying different foods, including complex dishes and foods from various cuisines, and addresses the variables taken into account when determining the calorie content of food items, including ingredient composition, portion size, and nutritional makeup. To enhance user experience and enable comprehensive calorie tracking, it explores real-time processing capabilities, user-friendly interfaces, and integration with other health and fitness platforms. Additionally, it provides a list of potential recipes. The interface developed in the proposed system is currently trained to identify and provide the calories of 100 food items, including basic food items, fruits, vegetables, and processed foods. The research work uses a real-time dataset for training and employs software such as YOLOv8, and TensorFlow for practical implementation.

Underutilized Vegetable Crops: Potential Sources of Nutrition and Livelihood Security

Vegetables are essential components of a balanced diet, offering a myriad of nutrients crucial for maintaining health and preventing diseases. Vegetable has low calorie counts and high fiber content, they aid in weight management by promoting satiety and controlling appetite. Underutilized vegetable crops are ones that are not widely cultivated and consumed compared to other vegetable crops. Underutilized vegetables play a significant role in enhancing dietary diversity, supporting local food systems, and fortifying food security. Cultivating underutilized vegetables enhances the biodiversity, resilience, and sustainability by reducing reliance on a limited range of crops, especially in the face of environmental challenges like diseases, pests, and climate change. Underutilized vegetables contribute to agricultural biodiversity, cultural heritage preservation, and economic opportunities for small-scale farmers. Embracing and promoting the cultivation, consumption, and conservation of underutilized vegetables are imperative for sustaining diverse diets, supporting sustainable agriculture, and addressing malnutrition and micronutrient deficiencies.

Effect of time restricted eating versus daily calorie restriction on sex hormones in males and females with obesity.

This study examined the effects of time restricted eating (TRE) on sex hormones in males and females, versus daily calorie restriction (CR). Adults with obesity (n = 90) were randomized to 1 of 3 groups for 12-months: 8-h TRE (eating only between 12:00 to 8:00 pm, with no calorie counting); CR (25% energy restriction daily); or control. Body weight decreased (P < 0.01) in the TRE and CR groups, relative to controls, in males, premenopausal females, and postmenopausal females, by month 12. Total testosterone, dehydroepiandrosterone (DHEA), and sex hormone binding globulin (SHBG) levels did not change over time, or between groups, in males, premenopausal females, and postmenopausal females. Estradiol, estrone, and progesterone were only measured in postmenopausal females, and remained unchanged. These findings suggest that TRE produces significant weight loss but does not impact circulating sex hormone levels in males and females with obesity over 12 months, relative to CR and controls.

Nutri-Check-A Food Image Recognition and Calorie Counter Website

Abstract: Nutri-Check is an innovative web-based platform designed to revolutionize dietary checking and calorie counting. This report provides an overview of the Nutri-Check platform, detailing its key features, functionalities and the underlying technology that powers its accurate food recognition and calorie counting capabilities. The primary goal of Nutri-Check is to simplify and enhance the process of monitoring dietary intake by allowing users to conveniently upload images of their meals. Leveraging state-of-the art image recognition algorithms, Nutri-Check identifies various food items within seconds, eliminating the need of manual entry of nutritional information. Nutri-Check employees deep learning and computer vision algorithms to accurately identify and categorize food items in uploaded images. Users receive instant feedback on the caloric content of their meals, aiding in better-informed dietary decisions. The Nutri-Check platform has the potential to significantly impact individuals’ health and wellness by promoting conscious and informed food choices

The Categorization of Continuous Attributes

ABSTRACTA continuous attribute (e.g., calorie count) can be classified into separate categories (e.g., high vs. low), and a similar attribute value can fall into different categories depending on where the category boundaries are drawn. This research explores the effect of categorization on judgments of options (e.g., products and incentive‐compatible games) with continuous attributes. I predict and find a systematic preference shift between two options that were presented with different categorization criteria: When two options involve a tradeoff between two continuous attributes, people tend to prefer the option with both attributes classified into the favorable categories given the categorization criteria. I further show that this effect is driven by larger perceived differences between attribute values across category boundaries and is moderated by people's tendency to rely on category information. Overall, this effect holds even when people are highly familiar with the attributes and feel confident to make similarity evaluations, when people are cued that the categories provide little informational value, and when people are incentivized to make deliberate decisions. The findings in this research carry both theoretical and practical implications.

Using a cross-platform application for optimizing nutrition in the training process of powerlifters

The article analyzes scientific developments in the field of powerlifters' training. It points out that there are unexplored areas, especially in the use of digital technologies for monitoring athletes' nutrition. We have developed a mobile application for optimizing the nutrition of powerlifters. Assistance was provided to athletes in installing the developed application and conducting instructions on its use. A survey was conducted among participants regarding their overall impression of the application's use among powerlifters and identifying aspects such as interface convenience, data collection, perceived reliability, and validity. It is noted that most users highly rate the application's functionality and capabilities, although there are certain aspects that require attention and possible improvements.&#x0D; For the category «Suggestions for Interface Improvement» the following subcategories were created: «Displaying measurement units for each item», «User instructions, manuals, pop-up tips», «Additional information when grouping food»,&#x0D; «Improving account settings», «Quick search for products and activities, product icons».&#x0D; For the category «Suggestions for Improving Program Functionality», the following subcategories were created: «Ability to add recipes, photos of dishes, diet planning, nutritional recommendations, diet templates», «Synchronization with other programs», «Choice of formula for basic metabolism, managing the thermal effect of food and activities», «Ability to download diagrams,' and «Ability to edit food and activities».&#x0D; Respondents highly appreciated the automatic calorie count, macronutrient settings, daily and weekly nutrition and activity tracking system, as well as the application's charts and their informativeness. This indicates the effectiveness of the developed functionality and the convenience of using the application. Two directions of proposed improvements that garnered the most interest among respondents were identified, such as «Ability to add recipes, photos of dishes, diet planning, nutritional recommendations, diet templates» and «User instructions, manuals, pop-up tips».&#x0D; Respondents noted that there is a certain reserve for improvements in the convenience and understandability of the application's interface, the completeness, diversity, and quality of functions, and the review of nutrition and activities for the week in the form of a list.

Abstract P190: Association of Meal Timing With Measures of Obesity: The Hispanic Community Health Study/Study of Latinos

Introduction: Time-restricted feeding has been associated with healthier weight, and as a weight-control intervention, can reduce caloric intake without calorie counting. Previous research showed that individuals with overweight who shortened their eating duration (time between first and last food intake of the day) experienced beneficial weight reduction. We explored this association in understudied US Hispanic/Latino individuals, as they experience a high prevalence of overweight and obesity. Hypothesis: We assessed the hypothesis that shorter eating duration is associated with healthier body mass index (BMI), percent body fat, or waist to hip ratio. Methods: We analyzed cross-sectional data from n=12079 Hispanic/Latino participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) who were not pregnant, not underweight, had reliable 24-hour dietary recall data, and had at least 3 accelerometer wear days. For each participant, we calculated eating duration, defined as the time between the first and last food intake of the day averaged over two 24-hour dietary recalls. We modeled eating duration in hours as the primary exposure in linear regression models with baseline measured BMI, percent body fat, or waist to hip ratio as outcomes of interest. We adjusted for age, sex, Hispanic background, field center, socioeconomic factors, sleep duration, glycemic status, diet quality, measured physical activity, and energy balance (ratio of energy intake to estimated energy needs). BMI was log transformed to help meet assumptions. Analyses accounted for complex survey design, missing accelerometer data, and accelerometer wear time. Results: Mean (SE) eating duration was 11.9 (0.04) hours. Those with longer eating duration tended to have higher energy intake (though less apparent for those with BMI at least 30), spend more time in moderate or vigorous physical activity, and were more likely to be employed full-time and perform shift work. After adjusting for energy balance and socioeconomic, medical and lifestyle factors, we found a significant positive association between eating duration and log-transformed BMI (regression coefficient 0.003 for eating duration in hours, SE 0.001, p=0.02). This significant association emerged only after adjusting for energy balance, demonstrating the importance of controlling for confounding between eating duration and intake. In sensitivity analysis, we excluded those with prevalent heart disease or diabetes, and obtained similar results. No statistically significant associations were noted between eating duration and the other obesity measures. Conclusions: Longer eating duration was associated with higher BMI in Hispanic/Latino persons after adjusting for covariates and energy balance from self-reported intake.

Fighting Classroom Hunger : Analysis of Mid-day Meal Scheme of Odisha

India State Hunger Index (ISHI) reported that, “India is home to the world’s largest food insecure population, with more than 200 million people who are hungry.” Adding to this, the report urged that, the country’s poor performance is driven by its high levels of child under-nutrition and poor calorie count. Education plays a vital role in the development of human potential. State Governments are spending considerable portion of their resources to provide educational facilities all over the country. In spite of these efforts, the goal of cent percent universalization of elementary education appears to be far and elusive due to inherent socio-economic factors present in the society. Free and compulsory education up to the age of 14 years is the constitutional commitment and it is estimated that primary school children (6-14 years) form about 20% of the total population. Poor school enrolment and high school dropout rate are attributed to the poor nutritional status of the children compounded by poor socio-economic condition, child labour and lack of motivation. The researchers have used empirical research to find the real gap in the system.

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity.

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity.

Adults Noticing Calorie Counts on Restaurant Menus: Evidence From Nationally Representative Data, 2022

IntroductionSince May 2018, federal restaurant menu labeling regulations have required large U.S. chain restaurants to disclose calorie counts on menus. This study estimates the share of U.S. adults who notice calorie information on fast-food and sit-down restaurant menus and identifies the consumer characteristics that predict noticing calorie labels. MethodsUsing a nationally representative sample of 5,185 U.S. adults aged 18 and older from the 2022 Health Information National Trends Survey (HINTS), linear regression models were estimated to predict the likelihood of noticing calorie labels the last time adults ordered food in a fast-food or sit-down restaurant. The 2022 HINTS data were publicly released in April 2023 and these public-use and de-identified data were analyzed in October 2023. ResultsIn 2022, about 1 in 2 U.S. adults (49.7%, 95% CI = 47.6%, 51.8%) reported noticing calorie labels during their last restaurant visit. The likelihood of noticing calorie information was significantly lower among men, lower income households, unpartnered adults, residents of the Northeast Census Region, and residents of rural areas. ConclusionsApproximately half of U.S. adults reported seeing calorie labels when they last ordered food in a fast-food or sit-down restaurant in 2022. Sex, income, marital status, and residential location influenced the likelihood of noticing calorie counts posted on restaurant menus.

Design and Realization of Calorify Mobile Application Interface with Augmented Reality Technology

A mobile smartphone is an integral part of the modern world, and not only for communication, but also for the possibility of using it for many other functions, from entertainment to security measures. An important components of mobile smartphone software are mobile applications, the demand for which is growing every year. One of the directions is mobile applications for maintenance, management, monitoring and support of a healthy lifestyle. This work is devoted to the development and implementation of the "fronend" part of the user interface software of the Calorify mobile application of a hybrid type intended for calorie counting. Despite the large number of mobile applications for counting calories, there is a need to develop a mobile application of a hybrid type with more ergonomic design solutions, confirmed by calculating calories based on analytical mathematical dependencies, with the implementation of augmented reality technology by scanning products. To realize the set goal, prototyping was first carried out in the Figma templating environment and the design of the future Calorify user interface was created. Next, modern UI toolkit technology was used in conjunction with the UI builder in the Unity engine to implement Calorify interfaces. UI Builder allows you to visually create and edit user interface resources, such as user interface documents (.uxml) and style sheets (.uss), used with the UI Toolkit. In general, the Calorify application consists of registration, user, main page and bottom menu pages. The scanner is located in the lower menu block, it is the main function of the Calorify application, which is the main difference and novelty of the developed mobile application. This button opens the option of taking a photo of the dish to automatically determine its calorie and nutritional value. This is a quick and convenient way to get product information the process of scanning products in Calorify, which implements augmented reality technology. For further development, it is planned to expand the possibility of registering domains of electronic addresses, to expand the database and filling of pages.

Healthism online: ‘What I eat in a day’ vlogs before and during COVID-19 restrictions

Objective and settingThe COVID-19 pandemic and its restrictions coincide with an increase in body weight and changes in health-related habits worldwide. This study focusses on the way health-related habits are portrayed online in digital food cultures. The study aims to investigate if and how the content of high-profile Dutch ‘What I eat in a day’ vlogs has changed during the first period of COVID-19 restrictions. We approach changes in digital food culture through the concept of ‘healthism’ and see vloggers as cultural intermediaries. Design and participantsWe collected the most watched vlogs of almost all high-profile Dutch influencers pre-post corona and analyzed these in a mixed method approach by using summative and thematic content analysis. ResultsPre-COVID vlogs highlight an explicit consciousness of energy balance-related behavior, focusing on calorie counting, avoidance of unhealthy food and the use of tracking apps. In vlogs uploaded in 2020, these themes are less present. Instead, intuitive eating and listening to one’s body are more central themes within the vlogs. ConclusionsWe consider the shift towards intuitive eating as another variant of “wellness diets” rather than a shift away from dieting, furthered by COVID-19 restrictions. The core values of health and self-regulation are upheld within the shift towards intuitive eating. Yet, we nuance the broad claims of healthism in biopolitics and point to relevant cultural changes within foodscapes.

The Impact of Restaurant Menu Calorie Labels on Restaurant Revenue and Profit: Evidence From a Randomized Controlled Trial

In 2018, the United States implemented a nationwide law requiring chain restaurants with more than 20 units to post calorie counts next to each of their menu items. Previously, individual cities, counties, and states had passed such laws, and certain chains had voluntarily posted calorie counts. Despite the widespread nature of this practice, the effect of calorie counts on restaurant outcomes is still not well understood. This paper estimates the impact of restaurant menu calorie labels on four important outcomes: 1) restaurant revenue; 2) restaurant profit; 3) the labor time of kitchen staff; and 4) patrons’ support for calorie labels. We estimate these impacts by conducting a randomized controlled experiment in two full-service restaurants. The results indicate that posting calorie counts on menus has no detectable negative impact on restaurants – the impacts on revenue, profit, and labor time are indistinguishable from zero. Moreover, exposure to the labels increases patrons’ support of restaurant menu calorie labels by 14.3% and reduces their opposition to them by 27.1%. Altogether, these results suggest that posting calorie counts does not harm restaurants, and are appealing to consumers.

Fast and Accurate Calorie Count Prediction from Food Images using a Convolution Neural Network Method

In the past ten years, with advances in deep learning techniques, automated object recognition has come very near to human levels of accuracy. Fast, automatic, and consistent image-based food calorie calculation is becoming a requirement with the increasing growth of overweight and other lifestyle- related disorders throughout the globe. Accurate and insightful solutions may be provided in the form of a mobile app with the aid of a deep learning-based automatic object recognition system. However, real-time image processing necessitates a high level of processing speed, which is a major consideration for such applications. Although several researchers have looked at estimating calories based on pictures of food, there is currently no image-driven, lightweight, rapid, and accurate food calorie estimation method. In this study, we offer a technique for recognizing common meals captured with a mobile phone camera by using Convolution Neural Networks (CNN) with optimum parameters. Calories and other nutritional information may be deduced from the known food class after the food items have been identified. Our research shows that our suggested method not only guarantees precision but also has the potential to greatly streamline the complex, time-consuming, and labor-intensive processes now used for estimating calorie intake by turning them together into real-time automation techniques.