Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Sep 16, 2021
Date Accepted: Mar 3, 2022
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Can Facial Morphology Determine Nutritional Status in the Elderly? Opportunities and Challenges.
ABSTRACT
Undiagnosed malnutrition is a significant problem in developed countries that can reduce quality of life for many individuals, particularly in the elderly. Moreover, it can also inflate the costs of existing healthcare systems due to the many metabolic complications it can cause. Current methods of assessing malnutrition can be cumbersome. It is required for a trained practitioner to be present to conduct an assessment, or that patients travel to facilities with specialised equipment to obtain their measurements. Therefore, digital healthcare is a possible way of closing this gap as it is fast gaining traction as a scalable means of improving efficiency in the healthcare system. It allows for nutritional status to be monitored remotely without requiring the physical presence of practitioners or the use of advanced medical equipment. As such there is an increasing interest to expand the range of digital applications so as to facilitate remote monitoring and management of health issues. In this paper, we discuss the feasibility of a novel digital remote method of diagnosing malnutrition using of facial morphometrics. Many malnutrition screening assessments include a subjective assessment of the head and 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, yet observable, changes through the use of facial morphometrics. Modern advancements in artificial intelligence, data science, sensors and computing technologies allow for facial features in the face to be accurately digitised, which could potentially allow these previously intuitive assessments to be quantified. This paper aims to stimulate further discussion and discourse on how this emerging technology can be used to provide real-time access to nutrition status. The use of facial morphometrics extends the use of currently available technology and may provide a scalable, easily deployable solution for nutrition status to be monitored in real-time. This will provide clinicians and dietitians the ability to keep track of patients remotely and provide the necessary intervention measures as required, as well as provide healthcare institutions and policy makers with essential information that can be utilised to inform and enable targeted public health approaches within affected populations.
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