Abstract
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.
Highlights
In recent decades, overweight and obesity has become a global health concern with significant economic and social implications [1,2,3,4,5,6]
Urbanization is associated with a combination of dysfunctional food systems, an adoption of Western diets, increased psychological stress and sedentary behaviors, leading to unhealthy environments that contribute to the development of chronic diseases [7,13,16]
Segmentation uses computer-vision tools such as Grubcut to define the borders and separate the respective foods in the image; classification uses deep learning principles such as Convolutional Neural Networks (CNN) to identify the foods; volume assessment involves the determination of the volume of the identified segmented foods; and lastly, nutrient derivation matches the assessed volume with density and nutrient datasets to calculate the nutrients or calories contained within the foods in the image
Summary
Overweight and obesity has become a global health concern with significant economic and social implications [1,2,3,4,5,6]. Urbanization is associated with a combination of dysfunctional food systems, an adoption of Western diets, increased psychological stress and sedentary behaviors, leading to unhealthy environments that contribute to the development of chronic diseases [7,13,16]. In countries such as Vietnam and Laos, exposure to urban environments have been associated with a three-fold increase in obesity [15]. The electronic search was supplemented by manual searches through the reference sections of selected publications, as well as with linked articles that were found to have cited these particular publications
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