Plant-based alternative proteins-are they nutritionally more advantageous?

BACKGROUND: The transition towards sustainable nutrition as well as the exploration of alternative sources of protein have been at the forefront of thinking in the 21st century. However, further research is required to ascertain if a diet composed of alternative plant-based proteins has similar nutritional advantages to a plant-based diet. This study aims to model the replacement of a diet consisting of animal-based proteins with plant-based alternatives (PBA), in a group of Asians. METHODS: A 4-day food record was collected from 50 individuals residing in Singapore and nutrient profiles were generated for each individual. Food records were analysed, and meat, dairy, and seafood ingredients were substituted gram-for-gram with their PBA. The original and replaced nutrient profiles were compared against each other and the differences in macro and micronutrients were analysed. RESULTS: A significant increase in carbohydrates, dietary fibre, as well as in micronutrients such as sodium and calcium was observed. Conversely, there was a significant decreased intake in overall energy, protein and fat (p < 0.005). CONCLUSIONS: The significant nutritional impact of substituting animal-based proteins for PBA may present benefits for bone health and individuals on a caloric restriction diet. However, higher sodium levels may be undesirable for individuals with cardiovascular conditions and hypertension, and the low bioavailability of iron in plant-based sources may present issues for iron deficient populations. Bearing some of these key findings in mind, researchers and manufacturers need to consider these when developing alternative protein products to meet consumer demands for palatable and nutritious plant-based products.

Use of Facial Morphology to Determine Nutritional Status in Older Adults: Opportunities and Challenges.

Undiagnosed malnutrition is a significant problem in high-income countries, which can reduce the quality of life of many individuals, particularly of older adults. Moreover, it can also inflate the costs of existing health care systems because of the many metabolic complications that it can cause. The current methods for assessing malnutrition can be cumbersome. A trained practitioner must be present to conduct an assessment, or patients must travel to facilities with specialized equipment to obtain their measurements. Therefore, digital health care is a possible way of closing this gap as it is rapidly gaining traction as a scalable means of improving efficiency in the health care system. It allows for the remote monitoring of nutritional status without requiring the physical presence of practitioners or the use of advanced medical equipment. As such, there is an increasing interest in expanding the range of digital applications to facilitate remote monitoring and management of health issues. In this study, we discuss the feasibility of a novel digital remote method for diagnosing malnutrition using facial morphometrics. Many malnutrition screening assessments include subjective assessments of the head and the face. Facial appearance is often used by clinicians as the first point of qualitative indication of health status. Hence, there may be merit in quantifying these subtle but observable changes using facial morphometrics. Modern advancements in artificial intelligence, data science, sensors, and computing technologies allow facial features to be accurately digitized, which could potentially allow these previously intuitive assessments to be quantified. This study aims to stimulate further discussion and discourse on how this emerging technology can be used to provide real-time access to nutritional status. The use of facial morphometrics extends the use of currently available technology and may provide a scalable, easily deployable solution for nutritional status to be monitored in real time. This will enable clinicians and dietitians to keep track of patients remotely and provide the necessary intervention measures as required, as well as providing health care institutions and policy makers with essential information that can be used to inform and enable targeted public health approaches within affected populations.

Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.

Obesity is a global health problem with wide-reaching economic and social implications. Nutrition surveillance systems are essential to understanding and addressing poor dietary practices. However, diets are incredibly diverse across populations and an accurate diagnosis of individualized nutritional issues is challenging. Current tools used in dietary assessment are cumbersome for users, and are only able to provide approximations of dietary information. Given the need for technological innovation, this paper reviews various novel digital methods for food volume estimation and explores the potential for adopting such technology in the Southeast Asian context. We discuss the current approaches to dietary assessment, as well as the potential opportunities that digital health can offer to the field. Recent advances in optics, computer vision and deep learning show promise in advancing the field of quantitative dietary assessment. The ease of access to the internet and the availability of smartphones with integrated cameras have expanded the toolsets available, and there is potential for automated food volume estimation to be developed and integrated as part of a digital dietary assessment tool. Such a tool may enable public health institutions to be able to gather an effective nutritional insight and combat the rising rates of obesity in the region.